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LIST OF ALL PUBLICATIONS

 

All publications in sections D-F are peer reviewed. In all joint papers (unless noted otherwise using the notations provided below) Prof. Angelov is the leading author who gave the basic idea, developed the approach. Three categories of papers (I-H) are provided in a separate page due to lack of space. The following notations are used: 

* a paper which was awarded best paper or a paper which was nominated for Outstanding Transactions award; 

† a collaborative work with a different team – shared credit

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A. Research monographic books (3):

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  1. P. Angelov, X. Gu, Empirical Approach to Machine Learning, Springer Nature, Switzerland, Dec. 2018, ISBN 978-3-030-02384-3, DOI: 10.1007/978-3-030-02384-3.

  2. P. Angelov, Autonomous Learning Systems: From Data Streams to Knowledge in Real time, John Willey and Sons, Dec. 2012, ISBN: 978-1-1199-5152-0.

  3. P. P. Angelov, Evolving Rule-based Models: A Tool for Design of Flexible Adaptive Systems, Springer-Verlag, Heidelberg, Germany, 2002, 215 pp., ISBN 3-7908-1457-1.

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B. Edited books (5)

  1. P. Angelov (Ed.), Handbook in Computer Learning and Intelligence, 2nd edition, World Scientific, 2 volumes, 1056 pp., DOI: 10.1142/12498, August 2022.

  2. P. Angelov (Ed.), Handbook in Computational Intelligence, World Scientific, 2 volumes, 870pp., 2016, ISBN: 978-0-470-28719-4.

  3. † P.P. Angelov, S. Sotirov (Eds.), Imprecision and Uncertainty in Information Representation and Processing: New tools based on Intuitionistic Fuzzy Sets and Generalized Nets, Jan 2016, Springer, 425 pp., ISBN: 9783319263014.

  4. P. Angelov (Ed.), Sense and Avoid in UAS: Research and Applications, 385pp., John Willey and Sons, May 2012, ISBN: 978-0-470-97975-4; (in addition to the English edition also in Chinese).

  5. P. Angelov, D. Filev and N. Kasabov (Eds.), Evolving Intelligent Systems: Methodology and Applications, 484 pp., John Willey and Sons, April 2010, ISBN: 978-0-470-28719-4.

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C. Patents (7)

Granted (3)

  1. P. Angelov, Machine Learning (Collaborative Systems), USA patent 8250004, granted 21 August 2012; priority date: 1 Nov. 2006; international filing date 23 Oct. 2007.

  2. P. Angelov, Anomalous System State Identification, USA patent 9390265, granted 12 July 2016; priority date 15 May 2012, GB1208542.9.

  3. † P. Angelov, R. Bruncak, D Hutchison, S Simpson, P Smith, System for identifying illegitimate communications between computers by comparing evolution of data flows, USA patent 9847924 (B2), granted 19 December 2017, priority date 2 April 2015.

Patent applications filed (4)

  1. P. Angelov, D. Kangin, Method and Apparatus for Deep Machine Learning, GB2314149.2; P365022GB, priority date 15 September 2023.

  2. P. Angelov, G. Morris, H. Parkinson, Transport Information Systems, PCT/GB2017/053586, filing date 28 November 2017; GB1620099.0, priority date 28 November 2016.

  3. P. Angelov, P. Sadeghi-Tehran, Data Structuring and Searching Method and Apparatus, GB1417807.3, priority date 8 October 2014.

  4. P. Angelov, D. Kolev. G. Markarian, System State Classifier, priority date October 2012, US14/677,269.

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D. Peer reviewed refereed journal papers (126):

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  1. X. Gu, P. Angelov, Q. Shen, Semi-supervised Fuzzily Weighted Adaptive Boosting for Classification, IEEE Transactions on Fuzzy Systems (IF 12.253), published on-line 4 January 2024, DOI: 10.1109/TFUZZ.2024.3349637.

  2. A, Shen, Y. Zhu, P. Angelov, R. Jiang, Marine Debris Detection in Satellite Surveillance using Attention Mechanisms, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (IF 5.5), published on-line 3 January 2024, DOI: 10.1109/JSTARS.2024.3349489.

  3. Z Jiang, H Rahmani, P. Angelov, R Vyas, H Zhou, S Black, B Williams, Deep orientated distance-transform network for geometric-aware centerline detection, Pattern Recognition (IF 7.196), v.146, 110028, DOI: 10.1016/j.patcog.2023.110028, published online 5 Oct. 2023.

  4. E. Soares, P. Angelov, S. Biaso, M. H. Froes, and D. K. Abe, A large dataset of real patients CT scans for SARS-CoV-2 identification, Evolving Systems (IF 2.347), DOI: 10.1007/s12530-023-09511-2, 2023.

  5. X. Gu, P. Angelov, J. Han, Q. Shen, Multilayer Evolving Fuzzy Neural Network, IEEE Transactions on Fuzzy Systems (IF 12.253), 13 May 2023, DOI: 10.1109/TFUZZ.2023.3276263.

  6. X. Gu, J. Han, Q. Shen, P. Angelov, Autonomous Learning for Fuzzy Systems: a review, Artificial Intelligence Review (IF 9.588), 10.1007/s10462-022-10355-6, published 15 Dec. 2022.

  7. M. Alghamdi, P. Angelov, A. Lopez Pellicer, Person Identification from Fingernails and Knuckles Images using Deep Learning Features and the Bray-Curtis Similarity Measure, Neurocomputing, (IF 5.779), 2022, 513, 83-93, 7 Nov. 2022.

  8. E. S. Yourdshahi, M. A. C. Alves, A. Varma, L. S. Marcolino, J. Ueyama, P. Angelov, On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork, Autonomous Agents and Multi-Agent Systems, 36 (2): 1-49, Oct. 2022  (IF 1.431).

  9. X. Gu, P. Angelov, Multiclass Fuzzily Weighted Adaptive Boosting-based Self-Organizing Fuzzy Inference Ensemble Systems for Classification, IEEE Transactions on Fuzzy Systems (IF 12.253), 30 (9): 3722-3735, Sept. 2022, DOI: 10.1109/TFUZZ.2021.3126116.

  10. X. Gu, P. P. Angelov, C. Zhang, P. M. Atkinson, A Semi-Supervised Deep Rule-Based Approach for Complex Satellite Sensor Image Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI (IF 24.314), 44(5): 2281-2292, DOI: 10.1109/TPAMI.2020.3048268, May 2022

  11. X. Gu, C. Zhang, Q. Shen, J. Han, P.P. Angelov, P.M. Atkinson, A Self-Training Hierarchical Prototype-based Ensem-ble Framework for Remote Sensing Scene Classification, Information Fusion (IF 17.564), v.80, 179-204, April 2022.

  12. Z. Jiang, Y. Wang, C.-T Li, P. Angelov, R. Jiang, Delve into Activations: Towards understanding Dying Neuron, IEEE Transactions on AI, 9 June 2022, DOI: 10.1109/TAI.2022.3180272

  13. X. Gu, P. Angelov, Q. Shen, Self-Organizing Fuzzy Belief Inference System for Classification, IEEE Transactions on Fuzzy Systems (IF 12.253), published online, 30 May 2022, DOI: 10.1109/ TFUZZ.2022.3179148.

  14. N. I. Arnold, P. Angelov, P. M. Atkinson, An Improved eXplainable Point Cloud Classifier (XPCC), IEEE Transactions on AI, published online on 22 Feb. 2022, DOI: 10.1109/TAI.2022.3150647

  15. R. Vyas, B. M. Williams, H. Rahmani, R. Boswell-Challand, Z. Jiang, P. Angelov, S. Black, Ensemble-based bounding box regression for enhanced knuckle localization, Sensors, (IF 3.847),  22(4):1569, 17 Feb. 2022

  16. Z. Yang, H. Rong, P. Wong, P. Angelov, C. Vong, C. Chiu, Z. Yang, A Novel Multiple Feature-based Engine Knock Detection System using Sparse Bayesian Extreme Learning Machine, Cognitive Computation (IF 4.89), published online 19 January 2022, DOI: 10.1007/s12559-021-09945-3.

  17. P. Angelov, E. A. Soares, Detecting and Learning from Unknown by Extremely Weak Supervision: eXploratory Classifier (xClass), Neural Computing and Applications (IF 5.102), v.33 (22), 15145-15157, November, 2021.

  18. Z.-X. Yang, H.-J. Rong, P. Angelov, Z.-X. Yang, Statistically Evolving Fuzzy Inference System for Non-Gaussian Noises, IEEE Transactions on Fuzzy Systems (IF 12.253), published online 22 June 2021, DOI: 10.1109/TFUZZ.2021.3090898.

  19. X. Gu, P. P. Angelov, Z. Zhao, Self-organizing fuzzy inference ensemble system for big streaming data classification, Knowledge-Based Systems (IF 8.14), vol. 218, 106870, published online on 22 April 2021, DOI. 10.1016/j.knosys.2021.106870.

  20. E. A. Soares, P. Angelov, X. Gu, Autonomous Learning Multiple-Model Zero-Order Classifier for Heart Sound Classification, Applied Soft Computing (IF 8.263), v.94, published online Sept. 2020, DOI: 10.1016/j.asoc.2020.106449.

  21. X. Gu, P. Angelov, Highly Interpretable Hierarchical Deep Rule-based Classifier, Applied Soft Computing (IF 8.263), v.92, published online July 2020, DOI.org/10.1016/j.asoc.2020.106310.

  22. J. Huang, P. P. Angelov, C. Yin, Interpretable policies for reinforcement learning by empirical fuzzy sets, Engineering Applications of Artificial Intelligence (IF 7.802), v.91, published online 1 May 2020, DOI.org/10.1016/j.engappai.2020.103559.

  23. E. Soares, P. Angelov, M. P. G. Castro, S. Nageshrao, B. Costa, D. Filev, Explaining Deep Learning Models Through Rule-Based Approximation and Visualization, IEEE Transactions on Fuzzy Systems (IF 12.253), v.29 (8): 2399-2407, DOI: 10.1109/TFUZZ.2020.2999776, Aug. 2021.

  24. Firouzi, B. Farahani, M. Daneshmand, K. Grise, J. S. Song, R. Saracco, L. L. Wang, K. Lo, P. Angelov, E. Soares, P.-S. Loh, Z. Talebpour, R. Moradi, M. Goodarzi, H. Ashraf, M. Talebpour, A. Talebpour, L. Romeo, R. Das, H. Heidari, D. Pasquale, J. Moody, C. Woods, E. S. Huang, P. Barnaghi, M. Sarrafzadeh, R. Li, K. L. Beck, O. Isayev, G. Tso, A. Kannan, R. Hergenrder and A. Luo, Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World, IEEE Internet of Things Journal (IF 10.238), v.8 (16), 12826-12846, DOI: 10.1109/JIOT.2021.3073904, 15 Aug. 2021.

  25. P. P. Angelov, E. A. Soares, R. Jiang, N. I. Arnold, P. M. Atkinson, Explainable artificial intelligence: an analytical re-view, WIREs Data Mining and Knowledge Discovery (IF 10.38), DOI:10.1002/widm.1424, publ. online 12 July 2021.

  26. Z. H. Yang, H. J. Rong, P. K. Wong, P. Angelov, Z. X. Yang, H. Wang, Self-evolving Data Cloud-based PID-like Controller for Nonlinear Uncertain Systems, IEEE Transactions on Industrial Electronics (IF 8.162), v.68 (5): 4508-4518, May 2021, DOI: 10.1109/TIE.2020.2982094.

  27. N. Arnold, P. Angelov, T. Viney, P. M. Atkinson, Automatic Extraction and Labelling of Memorial Objects From 3D Point Clouds, Journal of Computer Applications in Archaeology, v.4(1): 79-93, April 2021, DOI: 10.5334/jcaa.66.

  28. X. Gu, Q. Shen, P. Angelov, Particle Swarm Optimized Autonomous Learning Fuzzy System, IEEE Transactions on Cybernetics (IF 11.45), DOI: 10.1109/TCYB.2020.2967462, published online 20 Feb. 2020.

  29. A. B. Sargano, X. Gu, P. Angelov, Z. Habib, Human Action Recognition Using Deep Rule-Based Classifier, Multimedia Tools and Applications (IF 2.76), 79: 30653-30667, 1 Nov 2020.

  30. E. A. Soares, P. Angelov, Towards Explainable Deep Neural Networks (xDNN), Neural Networks (IF 8.05), 130: 185-194, Oct. 2020.

  31. C.-Y. Chiang, C. Barnes, P. Angelov, R. Jiang, Deep Learning-based Automated Forest Health Diagnosis from Aerial Images for Climate Change Monitoring, IEEE Access (IF 4.1), v.8:144064-144076, 28 July 2020.

  32. C. G. Bezerra, B. S. J. Costa, L. A. Guedes, P. P. Angelov, An Evolving Approach to Data Streams Clustering Based on Typicality and Eccentricity Data Analytics, Information Sciences (IF 6.795), 518:13-28, May 2020

  33. X. Gu, P. P. Angelov, E. A. Soares, A Self-adaptive Synthetic over-sampling technique for imbalanced classification, International Journal on Intelligent Systems (IF 8.71), v.35: 923-943, 23 Feb. 2020, DOI: 10.1002/int.22230.

  34. X. Gu, P. Angelov, H. J. Rong, Local Optimality of Zero-Order Autonomous Learning Neuro-Fuzzy Systems, Information Sciences (IF 6.795), 503: 351-380, 2019.

  35. X. Gu, P. Angelov, Z. Zhao, A distance-type-insensitive clustering approach, Applied Soft Computing (IF 6.73), v.77: 622-634, April 2019.

  36. P. Sadeghi-Tehran, P. Angelov, N. Virlet, M. Hawkesford, Scalable Database Indexing and Fast Image Retrieval based on Deep Learning and Hierarchical Nested Structure Applied to Remote Sensing and Plant Biology, Journal of Imaging (IF 3.81), v.5(3) 33:1-21, 2019.33; DOI:10.3390/jimaging5030033

  37. X. Gu, P. Angelov, Self-boosting first-order autonomous learning fuzzy systems, Applied Soft Computing (IF 6.73), 77: 118-134, 2019.

  38. P. Angelov, X. Gu, J. Principe, A generalized methodology for data analysis, IEEE Transactions on Cybernetics (IF 11.45), 48(10): 2981-2993, Oct. 2018.

  39. H.-J. Rong, P. Angelov, X. Gu, J. Bai, Stability of Evolving Fuzzy Systems based on Data Clouds, IEEE Transactions on Fuzzy Systems (IF 12.03), 26(5): 2774-2784, Oct. 2018.

  40. X. Gu, P. Angelov, J. Principe, A method for autonomous data partitioning into data clouds, Information Sciences, vol. 460-461, pp. 65-82 (IF 6.795), Sept. 2018.

  41. P. Angelov, X. Gu, Towards Anthropomorphic Machine Learning, IEEE Computer (IF 3.564), 51 (9): 18-27, Sept. 2018.

  42. P. Angelov, X. Gu, J. Principe, Autonomous learning multi-model systems from data streams, IEEE Transactions on Fuzzy Systems, (IF 12.03), 26(4): 2213-2224, Aug. 2018.

  43. P. Angelov, X. Gu, Deep rule-based classifier with human-level performance and characteristics, Information Sciences (IF 6.795), 463-464: 196-213, October 2018.

  44. † R. Bao, H. Rong, P. Angelov, B. Chen, P. Wong, Correntropy-Based Evolving Fuzzy Neural System, IEEE Transactions on Fuzzy Systems (IF 12.03), 26(3): 1324-1338, 23 June 2017.

  45. X. Gu, P. Angelov, Semi-supervised deep rule-based approach for image classification, Applied Soft Computing (IF 6.73), 68: 53-68, 2018.

  46. X. Gu, P. Angelov, Self-organising fuzzy logic classifier, Information Sciences (IF 6.795), 447, 36-51, 2018.

  47. X. Gu, P. Angelov, C. Zhang, P. Atkinson, A massively parallel deep rule-based ensemble classifier for remote sensing scenes, IEEE Geoscience and Remote Sensing Letters (IF 4.89), 15 (3), 345-349, 2018.

  48. J. Rubio, E. Lughofer, P. Angelov, J. F. Novoa, J. A. Meda-Campaña, A novel algorithm for the modeling of complex processes, Kybernetika (IF 1.05),  54 (1), 79-95, 2018.

  49. A. M. Ali, P. Angelov, Anomalous Behaviour Detection Based on Heterogeneous Data and Data Fusion, Soft Computing (IF 3.64), 22(10): 3187-3201, May 2018.

  50. † M. Pratama, P. Angelov, E. Lughofer, M. J. Er, Parsimonious Random Vector Functional Link Network for Data Streams, Information Sciences (IF 6.795), 430-431: 519-537, March 2018.

  51. P. Angelov, X. Gu, Empirical Fuzzy Sets, International Journal of Intelligent Systems (IF 8.71), 33(2): 362-395, Feb.2018; top20 most downloadable article

  52. X. Gu, P. Angelov, D. Kangin, J. Principe, Self-organised direction aware data partitioning algorithm, Information Sciences (IF 6.795), 423: 80-95, Jan. 2018.

  53. X. Gu, P. Angelov, D. Kangin, J. Principe, A new type of distance metric and its use for clustering, Evolving Systems (IF 1.91), 8(3): 167-177, 2017.

  54. J. Iglesias, A. Ledezma, A. Sanchis, P. Angelov, Real-Time Recognition of Calling Pattern and Behaviour of Mobile Phone Users through Anomaly Detection and Dynamically-Evolving Clustering, Applied Sciences (IF 2.68), 7(8):798, 2017.

  55. P. Angelov, P. Sadeghi-Tehran, C. Clarke, AURORA: autonomous real-time on-board video analytics, Neural Computing and Applications (IF 5.61), 28(5): 855-865, 2017.

  56. P. Angelov, X.  Gu, J. Iglesias, A. Ledezma, A. Sanchis, O. Sipele, R. Ramezani, Cybernetics of the mind: lear-ning individual's perceptions autonomously, IEEE Systems, Man, and Cybernetics Magazine, 3(2): 6-17, 2017

  57. R. Hyde, P. Angelov, A. MacKenzie, Fully online clustering of evolving data streams into arbitrarily shaped clusters, Information Sciences (IF 6.795), 382: 96-114, 2017.

  58. P. Angelov, X.  Gu, D. Kangin, Empirical data analytics, International Journal of Intelligent Systems (IF 8.71), 32(12): 1261-1284, Dec. 2017; top20 most downloadable article

  59. A. Sargano, P. Angelov, Z. Habib, A comprehensive review on handcrafted and learning-based action representation approaches for human activity recognition, Applied Sciences (IF 2.68), 7(1): 110, 2017.

  60. † N. Harris, L. Carpenter, J. Lee, G. Vaughan, M. Filus, R. Jones, B. OuYang, J. Pyle,  A. Robin-son, S. Andrews, A. Lewis, J. Minaeian, A. Vaughan, J. Dorsey, M. Gallagher, M. Le Breton, R. Newton, C. Percival, H. Ricketts, S. Bauguitte, G. Nott, A. Wellpott, M. Ashfold, J. Flemming, R. Butler, P. Palmer, P. Kaye, C. Stopford, C. Chemel, H. Boesch, N. Humpage, A. Vick, A. Mac Kenzie, R. Hyde, P. Angelov, E. Meneguz, A. Manning, Coordinated Airborne Studies in the Tropics (CAST), Bulletin of the American Meteorological Society (IF 8.166), 98(1): 145-162, 2017.

  61. P. Angelov, P. Sadeghi‐Tehran, Look‐a‐Like: A Fast Content‐Based Image Retrieval Approach Using a Hierarchically Nested Dynamically Evolving Image Clouds and Recursive Local Data Density, International Journal of Intelligent Systems (IF 8.71), 32(1): 82-103, 2017.

  62. G. Andonovski, P. Angelov, S. Blažič, I. Škrjanc, A practical implementation of Robust Evolving Cloud-based Controller with normalized data space for heat-exchanger plant, Applied Soft Computing (IF 6.73), 48: 29-38, 2016.

  63. C. Bezerra, B.  Costa, L. Guedes, P. Angelov, An evolving approach to unsupervised and Real-Time fault detection in industrial processes, Expert Systems with Applications (IF 6.954), 63: 134-144, 2016.

  64. A. Sargano, P. Angelov, Z. Habib, Human action recognition from multiple views based on view-invariant feature descriptor using support vector machines, Applied Sciences (IF 2.68), 6(10): 309,  2016.

  65. D. Kangin, P. Angelov, J. Iglesias, Autonomously evolving classifier TEDAClass, Information Sciences (IF 6.795), 366: 1-11, 2016.

  66. R. Precup, H. Hellendoorn, P. Angelov, Synergy of computers, cognition, communication and control with industrial applications, Computers in Industry (IF 7.64), 74: 71-74, 2015.

  67. R. Precup, P. Angelov, B. Costa, M. Sayed-Mouchaweh, An overview on fault diagnosis and nature-inspired optimal control of industrial process applications, Computers in Industry (IF 7.64), 74: 75-94, 2015.

  68. B. S. J. Costa, P. Angelov, L. A. Guedes, Fully unsupervised fault detection and identification based on recur-sive density estimation and self-evolving cloud-based classifier, Neurocomputing (IF 5.72), 150A: 289-303, 2015.

  69. C. Clarke, P. Angelov, Y. Majid, P. Sadeghi-Tehran, SARIVA: Smartphone App for Real-time Intelligent Video Analytics, Journal of Automation, Mobile Robotics and Intelligent Systems (IF 0.54), 8(4): 15-19, 2014.

  70. B. S. J. Costa, P. P. Angelov, L. A. Guedes, Real-Time Fault Detection using Recursive Density Estimation, Journal of Control, Automation and Electrical Systems (IF 1.56), ISSN: 2195-3880, 25 (4): 428-437, 2014.

  71. † J. Trevisan, J. Park, P. P. Angelov, A. A. Ahmadzai, K. Gajjar, A. D. Scott, P. L. Carmichael, F. L. Martin, Measuring similarity and improving stability in biomarker identification methods applied to Fourier-transform infrared (FTIR) spectroscopy, Journal of Biophotonics (IF 3.21), 7(3-4): 254-265, 2014.

  72. † M. Pratama, S. Anavatti, P. Angelov, E. Lughofer, PANFIS: A Novel Incremental Learning Machine, IEEE Trans. on Neural Networks and Learning Systems (IF 8.793), 25 (1): 55-68, 2014.

  73. P. Angelov, Outside the box: An Alternative Data Analytics Framework, Journal of Automation, Mobile Robotics and Intelligent Systems (IF 0.54), 8(2):29-35, 2014.

  74. R. D. Baruah, P. Angelov, DEC: Dynamically Evolving Clustering Autonomous and its Application to Structure Identification of Evolving Fuzzy Models, IEEE Transactions on Cybernetics (IF 11.45), 44(9): 1619-1631, 2013

  75. R. D. Baruah, P. Angelov, Analysis of Evolving Social Network: Methods and Results from Cell Phone Data Set Case Study, Intern. Journal of Social Network Mining (IF 3.87), ISSN 1757-8485, 1(3): 254-279, 2013

  76. P. Angelov, R. Yager, Density-based Averaging - a new Operator for Data Fusion, Information Sciences (IF 6.795), 222: 163-174, 2013.

  77. J. Trevisan, P. P. Angelov, A. D. Scott, P. L. Carmichael, F. L. Martin, IRootLab: a free and open-source MAT-LAB toolbox for vibrational biospectroscopy data analysis, Bioinformatics (IF 5.61),  29 (8): 1095-1097, 2013.

  78. J. Andreu, P. Angelov, Towards generic human activity recognition for ubiquitous applica-tions, Journal of Ambient Intelligence and Human Computing (IF 7.104), 4(2): 155-156, 2013.

  79. J. Andreu, P. Angelov, An Evolving Machine Learning Method for Human Activity Recognition Systems, Journal of Ambient Intel. and Humanized Computing (IF 7.104), 4(2): 195-206, 2013.

  80. J. Iglesias, P. Angelov, A. Ledezma, A. Sanchis, Creating evolving user behavior profiles automatically, IEEE Transactions on Knowledge Data Engineering (IF 6.98), 24(5): 854-867, 2012.

  81. P. Angelov, R. Yager, A New Type of Simplified Fuzzy Rule-based Systems, International Journal of General Systems (IF 2.2), 41(2): 163-185, 2012.

  82. † J. Trevisan, P. P. Angelov, P. L. Carmichael, A. D. Scott and F. L. Martin, Extracting biological information with computational analysis of Fourier transform infrared (FTIR) bio-spectroscopy datasets: current practices to future perspectives, Analyst (IF 4.62), 137: 3202-3215, 2012.

  83. R. Dutta-Baruah, P. Angelov, Evolving Fuzzy Systems for Data Streams: A Survey, Data Mining and Knowledge Discovery (IF 7.25), 1(6): 461-476, 2011.

  84. P. Angelov, Fuzzily Connected Multi-Model Systems Evolving Autonomously from Data Streams, IEEE Transactions on Systems, Man, and Cybernetics - part B, Cybernetics (IF 11.45), 41(4): 898-910, 2011.

  85. † J. J. Macias-Hernandez, P. Angelov, X. W. Zhou, Crude Oil Distillation Side Streams, Fuzzy Model, Online Model Prediction, Applied Mechanics and Materials, 88-89: 432-437, 2011.

  86. P. Angelov, P. Sadeghi-Tehran, R. Ramezani, An Approach to Autonomous Novelty Detection and Object Tracking in Video Stream, International Journal of Intelligent Systems (IF 8.71), 26(3): 189-205, 2011.

  87. † J. de Jesús Rubio, P. Angelov, E. García, An uniformly stable backpropagation algorithm to train a feedforward neural network , IEEE Transactions on Neural Networks (IF 8.793), 22(3): 356-366, 2011.

  88. E. Lughofer, P. Angelov, Handling Drifts and Shifts in On-line Data Streams with Evolving Fuzzy Systems, Applied Soft Computing (IF 6.73), 11(2): 2057-2068, 2011.

  89. P. Sadeghi-Tehran, J. Andreu, P. Angelov, X. Zhou, Intelligent Leader-Follower Behaviour for Unmanned Ground-based Vehicles, Journal of Automation, Mobile Robotics and Intelligent Systems (IF 0.54), ISSN 1897-8649, 5(1): 1-11, 2011.

  90. J. Trevisan, P. P. Angelov, P. L. Carmichael, A. D. Scott and F. L. Martin, A computational protocol and software implementation (as a MATLAB application) for biomarker identification in infrared spectroscopy datasets, Nature Protocols (IF 17.24) Exchange, May 2010, DOI: 10.1038/nprot.2010.97.

  91. J. A. Iglesias, P. Angelov, A. Ledezma, A. Sanchis, Human Activity Recognition based on Evol-ving Fuzzy Systems, International Journal of Neural Systems (IF 5.87), 20(5): 355-364, 2010.

  92. † J. G. Kelly, P. Angelov, J. Trevisan, N. Vlachopoulou, E. Paraskevaidis, P.L. Martin-Hirsch, and M.L. Martin, Robust classification of low-grade cervical cytology following analysis with ATR-FTIR spectroscopy and subsequent application of self-learning classifier eClass, Journal of Analytical and Bio-analytical Chemistry (IF 4.14), 398(5): 2191-2201, 2010.

  93. † J. Trevisan, P. P. Angelov, et al., Syrian Hamster Embryo Assay (pH 6.7) Coupled with Infrared Spectroscopy and Chemometrics Towards Toxicological Assessment, Analyst (IF 4.62), 135(12): 3266–3272, 2010.

  94. P. Angelov, A. Kordon, Adaptive Inferential Sensors based on Evolving Fuzzy Models: An Industrial Case Study, IEEE Transactions on Systems, Man and Cybernetics-B (IF 11.45), 40(2): 529-539, 2010.

  95. J. A. Iglesias, P. Angelov, A. Ledezma, A. Sanchis, Evolving Classification of Agents' Behaviours: A General Approach, Evolving Systems (IF 1.91), ISSN 1868-6478, 1(3): 161-171, 2010.

  96. S. McDonald, P. Angelov, Evolving Takagi-Sugeno Model with Memory for Slow Processes, International Journal on Knowledge-based and Intelligent Systems (IF 1.84), ISSN:1327-2314, 14(1):11-19, 2010.

  97. *P. Angelov, X. Zhou, Evolving Fuzzy-Rule-based Classifiers from Data Streams, IEEE Transactions on Fuzzy Systems (IF 12.03), ISSN 1063-6706, 16(6): 1462-1475, 2008, Outstanding Transactions paper nomination

  98. P. Angelov, E. Lughofer and X. Zhou, Evolving Fuzzy Classifiers with Different Architectures, Fuzzy Sets and Systems (IF 3.34), 159, 3160-3182, 2008.

  99. J. Kelly, P. Angelov, M. J. Walsh, H. M. Pollock, M. A. Pitt, P. L. Martin-Hirsch and F. Martin, A Self-Learning Fuzzy Classifier with Feature Selection for Intelligent Interrogation of mid-IR Spectroscopy Data Derived from Different Categories of Exfoliative Cervical Cytology, International Journal on Computational Intelligence Research (IF 1.9), ISSN0974-1259, 4(4): 392–401, 2008

  100. J. A. Wright, Y. Zhang, P. P. Angelov, R. A. Buswell and V. I. Hanby, Evolutionary Synthesis of HVAC System Configurations: Algorithm Development, International Journal of HVAC Research, 14 (1): 33-55, 2008.

  101. P. Angelov, E. Lughofer, Data-driven evolving fuzzy systems using eTS and FLEXFIS: comparative analysis, International Journal of General Systems (IF 2.259), 37(1): 45-67, 2008.

  102. P. Angelov, V. Giglio, C. Guardiola, E. Lughofer and J. M. Lujan, An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches, Measurement Science and Technology (IF 1.86), 17 (7) 1809-1818, 2006.

  103. P. Angelov, C. Xydeas, Fuzzy Systems Design: Direct and Indirect Approaches, Soft Computing (IF 3.64), 10 (9): 836-849, 2006.

  104. C. Xydeas, P. Angelov, S. Chiao and M. Reoullas, Advances in EEG Signals Classification via Dependant HMM models and Evolving Fuzzy Classifiers, International Journal on Computers in Biology and Medicine (IF 4.59), 36 (10): 1064-1083, 2006.

  105. P. P. Angelov, A Fuzzy Controller with Evolving Structure, Information Sciences (IF 6.795), 161: 21-35, 2004.

  106. P. Angelov, D. Filev, An Approach to On-line Identification of Takagi-Sugeno Fuzzy Models, IEEE Transactions on System, Man, and Cybernetics, part B – Cybernetics (IF 11.45), 34 (1): 484-498, 2004.

  107. P. Angelov, An approach for fuzzy rule-base adaptation using on-line clustering, International Journal of Approximate Reasoning (IF 3.816), 35 (3): 275-289, 2004.

  108. P. Angelov, D. Filev, Flexible Models with Evolving Structure, International Journal of Intelligent Systems (IF 8.71), 19 (4): 327-340, 2004.

  109. P. Angelov, R. Buswell, Automatic Generation of Fuzzy Rule-based Models from Data by Genetic Algorithms, Information Sciences (IF 6.795), 150 (1/2): 17-31, 2003.

  110. P. Angelov, An Evolutionary Approach to Fuzzy Rule-based Model Synthesis using Rules Indices, Fuzzy Sets and Systems (IF 3.34), 137 (3): 325-338, 2003.

  111. M. Eftekhari, L. Marjanovic and P. Angelov, Design and Performance of a Rule-based Con-troller in a Naturally Ventilated Room, Computers in Industry (IF 7.64), 51(3): 299-326, 2003.

  112. P. Angelov, R. Buswell, Identification of Evolving Rule-based Models, IEEE Transactions on Fuzzy Systems (IF 12.03), 10 (5): 667-677, 2002.

  113. P. Angelov, Supplementary Crossover Operator for Genetic Algorithms based on the Centre-of-Gravity Paradigm, Control and Cybernetics, 30 (2) 159-176, 2001.

  114. P. Angelov, Multi-objective Optimisation in Air-Conditioning Systems: Comfort/Discomfort Definition by IF Sets, Notes on Intuitionistic Fuzzy Sets, ISSN 1310-4926, 7 (1) 10-23, 2001.

  115. P. Angelov, Evolving Fuzzy Rule-based Models, Journal of Chinese Institute of Industrial Engineers, Taiwan, ISSN 1017-0669, 17: 459-468, 2000.

  116. L. Chen, O. Bernard, G. Bastin and P. Angelov, Hybrid Modelling of Biotechnological Processes using Neural Networks, Control Engineering Practice (IF 3.475), 8(7):821-827, 2000.

  117. P. Angelov, Optimization in an Intuitionistic Fuzzy Environment, Fuzzy Sets and Systems (IF 3.34), 68: 301-306, 1997.

  118. P. Angelov, R. Guthke, A GA-based Approach to Optimization of Bioprocesses Described by Fuzzy Rules, Bioprocess and Biosystems Engineering (IF 3.21), 16: 299-301, 1997.

  119. P. Angelov, An Analytical Method for Solving a Type of Fuzzy Optimization Problems, Control and Cybernetics, 24 (3): 363-373, 1995.

  120. P. Angelov, Intuitionistic Fuzzy Optimization, Notes on Intuitionistic Fuzzy Sets, 1: 27-33, 1995, ISSN 1310-4926.

  121. P. Angelov, A Generalized Approach to Fuzzy Optimization, International Journal of Intelligent Systems (IF 8.71), 9 (4): 261-268, 1994.

  122. P. Angelov, Approximate Reasoning Based Optimization, Yugoslav Journal on Operations Research, ISSN 0354-0243, 4 (1): 11-17, 1994.

  123. P. Angelov, M. Petrov, Fuzzy Optimization of Laboratory Fermenters, Journal of Biotechnology and Biotechnological Equipment (IF 1.18), ISSN 1310-2818, 4: 60-63, 1994.

  124. P. Angelov, S. Tzonkov, Optimal Control of Biotechnological Processes Described by Fuzzy Sets, Journal of Process Control (IF 3.67), 3(3): 147-152, 1993.

  125. D. Filev, P. Angelov, Fuzzy Optimal Control, Fuzzy Sets and Systems (IF 3.34), 47(2): 151-156, 1992.

  126. D. Filev, P. Angelov, Optimal Control in a Fuzzy Environment, Yugoslav Journal on Operations Research, ISSN 0354-0243, 2(1): 33-43, 1992.

E. Peer reviewed papers published in refereed Conference Proceedings (167)​

​

  1. D. Kangin, A. Aghasanli, P. Angelov, Interpretable-through-prototypes deepfake detection for diffusion models, Workshop and Challenge on Deep Fake Detection, DFAD2023 within the International Conference on Computer Vision, ICCV 2023, 2 Oct. 2023, pp.467-474.

  2. Y. Li, P. Angelov, N. Suri, Fuzzy Detector Against Adversarial Attacks, 2023 IEEE Symposium on Computational Intelligence, SSCI-2023, Mexico City, Mexico, 5-8 Dec. 2023, pp.306-311, published online, 1 January 2024, DOI 10.1109/SSCI52147.2023.10372061.

  3. Z. Yu, Y. Lu, P. Angelov, N. Suri, PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework, 18th International Conference on Mobility, Sensing and Networking, Guangzhou, China, 14-16 December 2022, best paper award.

  4. Y. Li, P. Angelov, N. Suri, Domain Generalization and Feature Fusion for Cross-Domain Imperceptible Adversarial Attack Detection, 2023 International Joint Conference on Neural Networks (IJCNN-2023), Gold Coast, Australia, 18-23 June, 2023.

  5. M. C. Alves, E. S. Yourdshahi, A. Varma, L. S. Marcolino, J. Ueyama, P. Angelov, On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork, Proc. 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS, pp.140-142, May 2023,

  6. N. L. Baisa, B. Williams, H. Rahmani, P. Angelov, S. Black, Multi-branch with attention network for hand-based person recognition, International Conference on Pattern Recognition, ICPR 2022, pp.727-732, IEEE Press, Aug. 2022.

  7. E. Soares, P. Angelov, N. Suri, Similarity-based Deep Neural Network to Detect Imperceptible Adversarial Attacks, 2022 IEEE Symposium Series on Computational Intelligence (SCCI2022), 4-7 December 2022, Singapore, DOI: 10.1109/SSCI51031.2022.10022016.

  8. Z. Zhang, P. Angelov, E. Soares, N. Longepe, P.-P. Mathieu, An Interpretable Deep Semantic Segmentation Method for Earth Observation, 11th IEEE International Conference on Intelligent Systems, IS’22, Warsaw, Poland, 12-14 Oct 2022, DOI: 10.1109/IS57118.2022.10019621

  9. Z. Jiang, H. Rahmani, P. Angelov, S. Black, B. Williams, Graph-context Attention Networks for Size-varied Deep Graph Matching, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), 19-24 June 2022, New Orleans, USA, pp. 2343-2352.

  10. N. L. Baisa, Z. Jiang, R. Vyas, B. Williams, H. Rahmani, P. Angelov, S. Black, Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning, International conference on Image Processing, Tools and Applications (IPTA), 19-22 April 2022, Salzburg, Austria.

  11. M. Camargos and P. Angelov, State of Health and Lifetime Prediction of Lithium-ion Batteries using Self-learning Incremental Models, Proc. 7th European Conference of the Prognostics and Health Management Society, Turin, Italy, 6-8 July 2022, pp. 78-86, ISBN 978-1-936263-36-3.

  12. M. Alghamdi, P. Angelov, B. Williams, Automated Person Identification Framework Based on Fingernails and Dorsal Knuckle Patterns, 2021 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, 2021 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021), Orlando, FL USA, 3-7 Dec. 2021, DOI: 10.110/SSCI50451.2021.9659850

  13. R. Vyas, H. Rahmani, R. Boswell-Challand, P. Angelov, S. Black, B. M. Williams, Robust End-to-End Hand Identification via Holistic Multi-Unit Knuckle Recognition, 2021 IEEE International Joint Conference on Biometrics (IJCB), Aug. 2021, pp. 1-8

  14. M. Jaworski, L. Rutkowski, P. Angelov, Concept Drift Detection Using Autoencoders in Data Streams Processing, Proc. International Conference on AI and Soft Computing, 124-133, Oct. 2020, Springer, DOI: 10.1007/978-3-030-61401-0_12.

  15. T. Xia, Y. Q. Fu, N. Jin, P. Chazot, P. Angelov, R. Jiang, AI-enabled Microscopic Blood Analysis for Microfluidic COVID-19 Hematology, 5th Intern. Conference on Computational Intelligence and Applications (ICCIA), 98-102, June 2020, DOI:10.1109/ICCIA49625.2020.00026

  16. P. Angelov, E. Soares, Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference, IEEE Intern. Conf. on Systems, Man and Cybernetics, IEEE SMC2020, 11-14 Oct 2020, Toronto, Canada, pp.2092-2099.

  17. X. Gu, M. A. Khan, P. Angelov, B. Tiwary, E. S. Yourdshahi and Z.-X. Yang, A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion, 2020 World Congress on Computational Intelligence (WCCI2020), Glasgow, Scotland, 19-24 July 2020.

  18. X. Gu, P. Angelov, Deep Rule-Based Aerial Scene Classifier using High-Level Ensemble Feature Descriptor, 2019 International Joint Conference on Neural Networks (IJCNN2019), Budapest, Hungary, 14-19 July 2019, DOI: 10.1109/IJCNN.2019.8851838.

  19. E. Soares, P. Angelov, B. Costa, M. Castro, Actively Semi-Supervised Deep Rule-based Classifier Applied to Adverse Driving Scenarios, 2019 International Joint Conference on Neural Networks (IJCNN2019), Budapest, Hungary, 14-19 July 2019, DOI: 10.1109/IJCNN.2019.8851842.

  20. E. Soares, P. Angelov, D. Filev, B. Costa, M. Castro, S. Nageshrao, Explainable Density-based Approach for Self-driving actions classification, 2019 IEEE International Conference on Machine Learning and Applications (ICMLA), 16 Dec 2019, pp. 469-474.  

  21. E. Shafipour Yourdshahi, M. A. do C. Alves, L. S. Marcolino, P. Angelov, On-line Estimators for Ad-hoc Task Allocation, Proc. 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, G. Sukthankar (eds.), May 9–13, 2020, Auckland, New Zealand.

  22. M. Alghamdi, P. Angelov, R. Gimenez, M. Rufino, E. Soares, Self-Organising and Self-Learning Model for Soybean Yield Prediction, 6th International Conference on Social Networks Analysis, Management and Security (SNAMS), 22 Oct 2019, pp. 441-446. 

  23. X. Gu, P. Angelov, M. Khan, An Odometer-Free Approach for Unmanned Ground-based Vehicle Simultaneous Localization and Mapping, 26 Oct 2019, IEEE Nuclear Science Symposium and Medical Imaging Conference, 26 Oct 2019, Manchester, UK.

  24. X. Gu, P. P. Angelov, A Semi-supervised Deep Rule-based Approach for Remote Sensing Scene Classification, In: Oneto L., Navarin N., Sperduti A., Anguita D. (Eds.) Recent Advances in Big Data and Deep Learning. INNSBDDL 2019. Proc. International Neural Networks Society (P. Angelov, R. Kozma Eds.), vol 1., pp. 257-266, Springer, Cham, 2019, ISBN 978-3-030-16840-7.

  25. P. Angelov, How Best to Design Fuzzy Sets and Systems: In Memory of Prof. Lotfi A. Zadeh, In: (R. Fuler, S. Giove, F. Massulli Eds.) Fuzzy Logic and Applications, Lecture Notes in AI 11291, Springer Nature Switzerland AG, ISBN 978-3-030-12543-1, pp.236-239, 2019.

  26. R. S. Martins, P. Angelov, B. S. J. Costa, , Automatic Detection of Computer Network Traffic Anomalies based on Eccentricity Analysis, In Proc. 2018 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE2019 within the 2018 IEEE World Congress on Computational Intelligence, WCCI2018, Rio de Janeiro, Brazil, 9-14 July 2018, IEEE Xplore, ISBN 978-1-5090-6020-7, pp.1-8.

  27. Y. L. Yong, Y. Lee, X. Gu, P. P. Angelov, D. C. L. Ngo, E. Shafipour, Foreign currency exchange rate prediction using neuro-fuzzy systems, In: Procedia Computer Science, 144: 232-238, 2018.

  28. X. Gu, P. Angelov, A Deep Rule-based Approach for Satellite Scene Image Analysis, IEEE International Conference on Systems, Man and Cybernetics (IEEE SMC 2018), Miyazaki, Japan, 7-10 Oct. 2018, pp.2778-2783.

  29. E. S. Yourdshahi, P. P. Angelov, L. S. Marcolino, G. Tsianakas, Towards Evolving Cooperative Mapping for Large-Scale UAV Teams, 2018 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2018), Bangaluru, India, Nov. 2018, pp. 2262-2269.

  30. E. S. Yourdshahi, T.Pinder, G. Dhawan, L. S. Marcolino, P. Angelov, Towards Large Scale Ad-hoc Teamwork, 2018 IEEE International Conference on Agents (ICA), Singapore, pp.44-49.

  31. P. Angelov, X. Gu, A Cascade of Deep Learning Fuzzy Rule-based Image Classifier and SVM, 2017 IEEE Intern. Conf. on Systems, Man, and Cybernetics (SMC2017), Banff, Canada, pp.746-751.

  32. P. Angelov, X. Gu, MICE: Multi-layer multi-model images classifier ensemble, 2017 IEEE International Conference on Cybernetics, CYBCONF2017, Exeter, UK, 2017, pp. 1-8, DOI: 10.1109/CYBConf.2017.7985788.

  33. X. Wang, A. Ali, P. Angelov, Gender and Age Classification of Human Faces for Automatic Detection of Anomalous Human Behaviour, 2017 IEEE International Conference on Cybernetics (CYBCONF2017), Exeter, UK,  2017, pp.1-6, DOI: 10.1109/CYBConf.2017.7985780.

  34. G. Andonovski, P. Angelov, S. Blažič, I. Škrjanc, Robust Evolving Cloud-based Controller (RECCo), 2017 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS2017), Ljubljana, Slovenia, pp.  1-6, DOI: 10.1109/EAIS.2017.7954835, IEEE ALMA Competition winner.

  35. A. Sargano, X. Wang, P. Angelov, Z. Habib, Human action recognition using transfer learning with deep representations, 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, USA, 2017, pp. 463-469.

  36. † M. Pratama, P. Angelov, J. Lu, E. Lughofer, M. Seera, C. Lim, A randomized neural network for data streams, 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, USA, 2017, pp. 3423-3430.

  37. P. Angelov, X. Gu, J. Principe, Fast feedforward non-parametric deep learning network with automatic feature extraction, 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, USA, 2017, pp.  534-541.

  38. P. Angelov, X.  Gu, Autonomous Learning Multi-Model Classifier of 0-Order (ALMMo-0), 2017 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS-2017), Ljubljana, Slovenia, 2017, pp.  1-7.

  39. *X.  Gu, P. Angelov, Autonomous anomaly detection, 2017 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS-2017), Ljubljana, Slovenia, 2017, pp.  1-8.

  40. P. Angelov, X. Gu, Local modes-based free-shape data partitioning, 2016 IEEE Symposium Series on Computational Intelligence within SSCI2016, Athens, Greece, pp.1-8, DOI:10.1109/ SSCI.2016.7850117.

  41. X. Gu, P. Angelov, G. Gutierrez, J. Iglesias, A. Sanchis, Parallel computing TEDA for high frequency streaming data clustering, INNS Conference on Big Data, Thessaloniki, Greece, 2016, pp.238-253.

  42. X Gu, P. Angelov, Autonomous data-driven clustering for live data stream, IEEE International Conference on Systems, Man, and Cybernetics (SMC2016), Budapest, Hungary, 2016, pp. 001128 – 001135, DOI: 10.1109/SMC.2016.7844394.

  43. P. Angelov, X. Gu, D. Kangin, J. Principe, Empirical data analysis: a new tool for data analytics, IEEE International Conference on Systems, Man, and Cybernetics (SMC2016), Budapest, Hungary 2016, pp. 000052 – 000059, DOI: 10.1109/SMC.2016.7844219.

  44. B. Costa, C. Bezerra, L. Guedes, P. Angelov, Unsupervised classification of data streams based on Typicality and Eccentricity Data Analytics, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2016), Vancouver Canada, 2016, pp.58-63.

  45. A. Antoniou, P. Angelov, A general purpose intelligent surveillance system for mobile devices using deep learning, International Joint Conference on Neural Networks (IJCNN-2016), Vancouver Canada, 2016, pp.2879-2886. 

  46. P. Angelov, X. Gu, G. Gutierrez, J. Iglesias, A. Sanchis, Autonomous data density based clustering method, 2016 International Joint Conference on Neural Networks (IJCNN-2016), Vancouver Canada, 2016, pp.2405-2413.

  47. C. Bezerra, B.  Costa, L. Guedes, P. Angelov, A new evolving clustering algorithm for online data streams, 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Natal, Brazil, 2016, pp.162-168.

  48. X. Gu, P. Angelov, A. Ali, W. Gruver, G. Gaydadjiev, Online evolving fuzzy rule-based prediction model for high frequency trading financial data stream, 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS-2016), Natal, Brazil, 2016, pp.169 - 175.

  49. G. Morris, P. P. Angelov, Edge flow, 2015 IEEE International Conference on Systems, Man and Cybernetics, SMC 2015, Hong Kong, pp.1942-1948, DOI 10.1109/SMC.2015.339.

  50. G. Andonovski, S. Blazic, P.P. Angelov, I. Skrjanc, Analysis of Adaptation Law of the Robust Evolving Cloud-based Controller, Proc. 2015 IEEE International Conference on Evolving Intelligent Systems, EAIS-2015, 1-3 Dec. 2015, Douai, France, pp.1-7, DOI 10.1109/EAIS.2015.7368793.

  51. G. Andonovski, S. Blazic, P. P. Angelov, I. Skrjanc, Robust Evolving Cloud based Controller in Normalized Data Space for Heath Exchanger Plant, Proc. 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, pp.1-7, DOI 10.1109/FUZZ-IEEE.2015.7337992.

  52. C. G. Bezerra, B. S. J. Costa, L. A. Guedes, P. P. Angelov, A Comparative Study of Autonomous Learning Outlier Detection Methods Applied to Fault Detection, Proc. 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, pp.1-7, DOI 10.1109/FUZZ-IEEE.2015.7337939.

  53. D. Kangin, P. P. Angelov, Evolving Clustering, Classification and Regression with TEDA, 2015 IEEE International Joint Conference on Neural Networks, IJCNN2015, pp.1-8, DOI 10.1109/IJCNN.2015.7280528.

  54. B. S. J. Costa, C. G. Bezerra, L. A. Guedes, P. P. Angelov, Online Fault Detection based on Typicality and Eccentricity, 2015 IEEE International Joint Conference on Neural Networks, IJCNN 2015, pp.1-6, DOI 10.1109/IJCNN.2015.7280712.

  55. P. P. Angelov, Typicality Distribution Function: A New Density based Data Analytics Tool, 2015 IEEE International Joint Conference on Neural Networks, IJCNN 2015, pp.1-6, DOI 10.1109/IJCNN.2015.7280438, 11 citations.

  56. R. Hyde, P. Angelov, A New Online Clustering Approach for Data in Arbitrary Shaped Clusters, 2015 IEEE International Conference on Cybernetics, CYBCONF 2015, pp.228-233, DOI: 10.1109/CYBConf.2015.7175937.

  57. S. Blazic, P. Angelov, I. Skrjanc, Comparison Approaches for Identification of all-data cloud-based evolving systems, Proc. IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control, ESCIT/IFAC2015, pp.1-5.

  58. P. Angelov, Anomaly Detection based on Eccentricity Analysis, Proc. 2014 IEEE Symposium on Evolving and Autonomous Learning Systems, EALS within SSCI2014, Orlando, USA, 9-12 Dec. 2014, pp.1-8, ISBN 978-1-4799-4495-8.

  59. P. Sadeghi-Tehran, C. Clarke, P. Angelov, Real-time Approach for Autonomous Detection and Tracking of Moving Objects from UAV, Proc. 2014 IEEE Symposium on Evolving and Autonomous Learning Systems, EALS within SSCI2014, Orlando, FL, USA, 9-12 Dec. 2014, pp.43-49, ISBN 978-1-4799-4495-8, IEEE Xplore.

  60. P. Angelov, A. Wilding, RTSDE: Recursive Total-Sum-Distances-based Density Estimation Approach and its Application for Autonomous Real-time Video Analytics, Proc. 2014 IEEE Symposium on Evolving and Autonomous Learning Systems, EALS within SSCI2014, Orlando, FL, USA, 9-12 December 2014, pp. 81-86, ISBN 978-1-4799-4495-8, IEEE Xplore.

  61. R. Hyde, P. Angelov, A Fully Autonomous Data Density Based Clustering Technique, Proc. 2014 IEEE Symposium on Evolving and Autonomous Learning Systems, EALS within SSCI2014, Orlando, FL, USA, 9-12 Dec. 2014, pp.116-123, ISBN 978-1-4799-4495-8.

  62. G. Morris, P. Angelov, Real-time novelty detection in video using background subtraction techniques: State of the art a practical review, Proc. IEEE International Conference on Systems, Man and Cybernetics, SMC2014, 5-8 October 2014, San Diego, USA, pp.537-543.

  63. R. Hyde, P. Angelov, Data Density based Clustering, 14th UK Workshop on Computational Intelligence, UKCI2014, 9-10 September 2014, Bradford, UK, pp.1-7.

  64. R. D. Baruah, P. Angelov, D. Baruah, Dynamically Evolving Fuzzy Classifier for Real-time Classification of Data Streams, Proc. 2014 World Congress on Computational Intelligence, WCCI-2014, 6-11 July 2014, Beijing, China, pp.383-389.

  65. B. S. J. Costa, P. Angelov, L. A. Guedes, A new Unsupervised Approach to Fault Detection and Identification, Proc. 2014 World Congress on Computational Intelligence, WCCI-2014, 6-11 July 2014, Beijing, China, pp.1557-1564.

  66. R. D. Baruah, P. Angelov, D. Baruah, Dynamically Evolving Clustering for Data Streams, In Proc. 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2014, 2-4 June, 2014, Linz, Austria, DOI 10.1109/EAIS.2014.6867473.

  67. I. Skrjanc, S. Blazic, P. Angelov, Robust evolving cloud-based PID control adjusted by gradient learning method, Proc. 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2014, 2-4 June, 2014, Linz, Austria, pp.1-8.

  68. P. Angelov, D. Kangin, X. Zhou, D. Kolev, Symbol Recognition with a new Autonomously Evolving Classifier AutoClass, In Proc. 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2014, 2-4 June, 2014, Linz, Austria, pp.1-7, DOI 10.1109/EAIS.2014.6867482.

  69. R. D. Baruah, P. Angelov, Online Learning and Prediction of Data streams using Dynamically Evolving Fuzzy Approach, Proc. 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE2013,pp.1-8, ISBN978-1-4799-0020-6, DOI:10.1109/FUZZ-IEEE.2013.6622517.

  70. M. Suvorov, S. Ivliev, G. Markarian, D. Kolev, D. Zvikhachevskiy, P. Angelov, Incremental Anomaly Identification by Adapted SVM Method, Proc. International Joint Conference on Neural Networks, IJCNN-2013, Dallas, TX, USA, 3-9 August, 2013, ISBN: 978-1-4673-6129-3.

  71. *B. Costa, I. Skrjanc, S. Blazic, P. Angelov, A practical implementation of self-evolving cloud-based control of a pilot plant, Proc. 2013 IEEE International Conference on Cybernetics, CYBCONF-2013, Lausanne, Switzerland, pp.7-12, 13-15 June, 2013, ISBN: 978-1-4673-6469-0/13, best student paper award.

  72. P. Angelov, I. Skrjanc and S. Blazic, Robust Evolving Cloud-based Controller for a Hydraulic Plant, Proc. IEEE Symposium Series on Computational Intelligence SSCI-2013,16-19 April 2013, Singapore, IEEE Press, ISBN 978-1-4673-5855-2/13, pp.1-8.

  73. D. Kolev, P. Angelov, G. Markarian, M. Suvorov and S. Lysanov, ARFA: Automated Real-time Flight Data Analysis using Evolving Clustering, Classifiers and Recursive Density Estimation, Proc. IEEE Symposium Series on Computational Intelligence, SSCI-2013, 16-19 April 2013, Singapore, ISBN 978-1-4673-5855-2/13, pp. 91-97.

  74. A. Ali, D. Hutchison, P. Angelov, P. Smith, Towards an autonomous resilience strategy the implementation of a self-evolving rate limiter, Proc. 13th UK Workshop on Computational Intelligence, UKCI2013, Manchester, UK, pp. 299-304.

  75. R. D. Baruah, P. Angelov, Evolving Local Means Method for Clustering of Streaming Data, In Proc. 2012 World Congress on Computational Intelligence, WCCI-2012, 10-15 June 2012, Brisbane, Australia, pp.2161-2168 (IEEE Press ISBN 978-1-4673-1489-3).

  76. P. Sadeghi-Tehran, A. B. Cara, P. Angelov, H. Pomares, I. Rojas, A. Prieto, Self-Evolving Parameter-free Rule-based Controller, 2012 World Congress on Computational Intelligence, WCCI2012, 10-15 June 2012, Brisbane, Australia, pp.754-761, ISBN 978-1-4673-1489-3.

  77. P. Angelov, J. Andreu, T. Vong, Automatic Mobile Photographer and Assisted Picture Diary for Memory Aid, 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2012, 17-18 May 2012, Madrid, Spain, pp. 102-107, ISBN 978-1-4673-1727-6.

  78. P. Sadeghi-Tehran, S. Behera, P. Angelov, J. Andreu, Autonomous Visual Self-Localization in Completely Unknown Environment, 2012 IEEE Conference on Evolving and Adaptive Intel-ligent Systems, EAIS-2012, 17-18 May 2012, Madrid, Spain, pp.90-95, ISBN978-1-4673-1727-6

  79. R. D. Baruah, P. Angelov, Evolving Social Network Analysis: A Case Study on Mobile Phone Data, In Proc. 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2012, 17-18 May 2012, Madrid, Spain, pp. 114-120, ISBN 978-1-4673-1727-6.

  80. P. Sadeghi-Tehran, P. Angelov, A Real-time Approach for Novelty Detection and Trajectories Analysis for Anomaly Recognition in Video Surveillance Systems, 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS-2012, 17-18 May 2012, Madrid, Spain, pp. 108-113, ISBN 978-1-4673-1727-6.

  81. P. Angelov, C. Gude, P. Sadeghi-Tehran, T. Ivanov, ARTOT: Autonomous Real-Time Object Detection and Tracking by a Moving Camera, In Proc. 2012 IEEE Conference on Intelligent Systems, IS-12, 6-8 September, 2012, Sofia, Bulgaria, pp. 446-452.

  82. A. Azman, D. Hutchison, P. Angelov, P. Smith, Adaptive Resilience of Computer Networks, 4th International Workshop on Reliable Networks Design and Modeling, St Petersburgh, Russia, 2012.

  83. P. P. Angelov, Autonomous Machine Learning (ALMA): Generating Rules from Data Streams, In Proc. Special International Conference on Complex Systems, COSY-2011, 16-19 September 2011, Ohrid, Former Yugoslav Republic of Macedonia, pp. 249-256.

  84. J. Andreu, P. Angelov, R. D. Baruah, Real-time Recognition of Human Activities from Wearable Sensors by Evolving Classifiers, Proc. 2011 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2011, 27-30 June, 2011, Taiwan, ISSN 978-1-4244-7317-5/11, pp. 2786-2793.

  85. J. Andreu, R. Dutta Baruah, P. P. Angelov, Automatic scene recognition for low-resource devices using evolving classifiers, Proc. 2011 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE2011, 27-30 June, 2011, Taipei, Taiwan, ISSN 978-1-4244-7317-5/11, pp. 2779-2785

  86. R. Dutta-Baruah, P. Angelov, J. Andreu, Simpl_eClass: Simple Potential-free Evolving Fuzzy Rule-Based On-line Classifiers, Proc. 2011 IEEE International Conference on Systems, Man and Cybernetics, SMC 2011, Anchorage, Alaska, USA, 7-9 Oct, 2011, pp.2249-2254.

  87. A. Azman, P. Angelov, D. Hutchison, Towards an Adaptive Resilience Strategy for Future Computer Networks, Proc. UK Workshop on Computational Intelligence, UKCI 2011, 7-9 September, 2011, Manchester, UK, pp.201-206.

  88. P. Angelov, R. Yager, Simplified Fuzzy Rule-based Systems using Non-parametric Antecedents and relative Data Density, Proc. IEEE Symposium on Evolving and Adaptive Intelligent Systems, EAIS2011 within 2011 IEEE Series on Computational Intelligence, SSCI-2011,11-15 April 2011, Paris, France, pp.62-69, ISBN 978-1-4244-9977-9.

  89. A. Iglesias, P. Angelov, A. Ledezma, A. Sanchis, Evolving Human Activity Classifier from Sensor Streams, IEEE Symposium on Evolving and Adaptive Intelligent Systems, EAIS2011 within SSCI-2011, 11-15 April 2011, Paris, France, pp.139-146, ISBN 978-1-4244-9977-9.

  90. P. Sadeghi-Tehran, P. Angelov, Online Self-Evolving Fuzzy Controller for Autonomous Mobile Robots, Proc. IEEE Symposium on Evolving and Adaptive Intelligent Systems, EAIS2011 within  SSCI-2011,11-15 April 2011, Paris, France, pp.100-107, ISBN 978-1-4244-9977-9, IEEE Xplore.

  91. P. Angelov, R. Yager, A Simple Rule-based System through Vector Membership and Kernel-based Granulation, In: Proc. 5th International Conference on Intelligent Systems, IS-2010,7-9 July 2010, London, UK, IEEE Xplore, pp.349-354.

  92. P. Sadeghi-Tehran, P. Angelov, R. Ramezani, A Fast Approach to Autonomous Detection, Identification, and Tracking of Multiple Objects in Video Streams under Uncertainties, In Proc. International Conference on Information Processing and Management of Uncertainties, IPMU2010: E. Huellermeier, R. Kruse, and F. Hoffmann (Eds.), Part II, CCIS 81, pp. 30–43, 2010, ISBN 3-642-14057-2, Springer, ISSN 1865-0929.

  93. J. Andreu, P. Angelov, Real-Time Recognition from Wireless Sensors Using Evolving Fuzzy Systems, Proc. 2010 IEEE World Congress on Computational Intelligence,18-23 July 2010, Barcelona, Spain, pp.2652-2659, ISBN 978-1-4244-6920-8, IEEE Xplore.

  94. J. A. Iglesias, P. Angelov, A. Ledezema, A. Sanchis, User Modeling: Through Statistical Analysis and an Evolving Classifier, Proc. 2010 IEEE World Congress on Computational Intelligence, 18-23 July 2010, Barcelona, Spain, pp. 3226-3233, ISBN 978-1-4244-6920-8.

  95. J Andreu, P. Angelov, Forecasting time-series for NN GC1 using Evolving Takagi-Sugeno Fuzzy Systems with On-line Inputs Selection, Proc. 2010 IEEE World Congress on Computational Intelligence, 18-23 July 2010, Barcelona, Spain, pp.1479-1483, ISBN 978-1-4244-6920-8.

  96. J. A. Iglesias, P. Angelov, A. Ledezema, A. Sanchis, Human Activity Recognition in Intelligent Home Environments: An Evolving Approach, Proc. 19th European Conference on AI, ECAI 2010 (H. Coelho, R. Studer and M. Wooldridge Eds.), Lisbon, Portugal, 16-20 August 2010, IOS Press, ISSN: 0922-6389, pp. 1047-1048.

  97. R Dutta-Baruah, P. Angelov, Clustering as a Tool for Self-generation of Intelligent Systems: A Survey, Proc. International Conference on Evolving Intelligent Systems, EIS'10, April 2010, Leicester, UK, pp.34-41, ISBN 978-1902956947.

  98. *J. A. Iglesias, P. Angelov, A. Ledezema, A. Sanchis, Modelling Evolving User Behaviours, In Proc. 2009 IEEE Symposium on Evolving and Self-Developing Intelligent Systems, ESDIS within 2009 IEEE Series on Computational Intelligence, 29 March-2 April, 2009, Nashville, TN, USA, IEEE Xplore, ISBN: 978-1-4244-2754-3, pp.16-23, best paper award.

  99. E. Lughofer, P. Angelov, Detecting and Responding to Drift and Shift in On-line Data Streams with Evolving Fuzzy Systems, Proc. 2009 IFSA World Congress and 2009 EUSFLAT Conference, 19-23 July 2009, Lisbon, Portugal, ISBN 978-95079-6-8, pp.931-937.

  100. P. Angelov, X. Zhou, On Line Learning Fuzzy Rule-based System Structure from Data Streams, Proc. 2008 IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6, 2008, ISBN 978-1-4244-1821-3/08, pp.915-922, IEEE Xplore.

  101. P. Angelov, R. Ramezani, X. Zhou, Autonomous Novelty Detection and Object Tracking in Video Streams using Evolving Clustering and Takagi-Sugeno type Neuro-Fuzzy System, Proc. 2008 IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6, 2008, ISBN 978-1-4244-1821-3/08, pp.1457-1464, IEEE Xplore.

  102. R. Ramezani, P. Angelov, X. Zhou, A Fast Approach to Novelty Detection in Video Streams using Recursive Density Estimation, Proc. 4th International IEEE Symposium on Intelligent Syst, 6-8 Sept 2008, Varna, Bulgaria, ISBN978-1-4244-1739-1/08, v.II, pp.14-2 -- 14-7.

  103. S. McDonald, C. Xydeas, P. Angelov, Decision Support Systems - Improving levels of Care and Lowering the Costs in Anticoagulation Therapy, Proc. First International Conference on Electronic Healthcare for 21st Century, eHelath 2008, London, UK, 8-9 Sept 2008, pp.175-178.

  104. S. McDonald, C. Xydeas, P. Angelov, A Retrospective Comparative Study of three Data Modelling Techniques in Anticoagulation Therapy, Proc. 2008 International Conference on BioMedical Engineering and Informatics BMEI2008, 28-30 May 2008, Hainan, China, ISBN 978-0-7695-3118-2/08, pp. 219-225.

  105. X. Zhou, P. Angelov, C. Wang, A Predictive Controller for Object Tracking of a Mobile Robot, Proc. 5th International Conference on Informatics in Control, Automation, and Modelling, ICINCO-2008, Madeira, Portugal, 11-15 May 2008, ISBN 978-989-8111-34-0, pp.73-82.

  106. P. Angelov, A. Kordon, X. Zhou, Evolving Fuzzy Inferential Sensors for Process Industry, Proc. 3rd International Workshop on Genetic and Evolving Fuzzy Systems, 4-7 March, 2008, Witten-Bomerholz, Germany, ISBN 978-1-4244-1613-4, pp.41-46.

  107. P. Angelov, C. D. Bocaniala, C. Xydeas, C. Pattchet, D. Ansell, M. Everett, G. Leng, A Passive Approach to Autonomous Collision Detection and Avoidance in Uninhabited Aerial Systems, Proc. 10th Intern. Conf. on Computer Modelling & Simulation, 1-3 April 2008, Cambridge, UK, pp.64-69.

  108. P. Angelov, X. Zhou, E. Lughofer, D. Filev, Architectures of Evolving Fuzzy Rule-based Classifiers, Proc. 2007 IEEE International Conference on Systems, Man and Cybernetics, SMC-2007, Montreal, Canada, ISBN 1-4244-0991-8/07, pp.2050-2055, IEEE Xplore.

  109. J. J. Macias-Hernandez, P. Angelov, X. Zhou, Soft Sensor for Predicting Crude Oil Distillation Side Streams using Takagi Sugeno Evolving Fuzzy Models, Proc. 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC2007, 7-10 October, 2007, Montreal, Canada, ISBN 1-4244-0991-8/07, pp.3305-3310, IEEE Xplore.

  110. E. Lughofer, P. Angelov, X. Zhou, Evolving Single-and Multi-Model Fuzzy Classifiers with FLEXFIS-Class, Proc. 2007 IEEE International Conference on Fuzzy Systems, 23-26 July, 2007, London, ISBN 1-4244-1210-2/07, pp.363-368.

  111. P. Angelov, X. Zhou, F. Klawonn, Evolving Fuzzy Rule-based Classifiers, Proc. 2007 IEEE International Conference on Computational Intelligence Applications for Signal and Image Processing, April 1-5, 2007, Hawaii, USA, pp.220-225, IEEE Xplore.

  112. X. Zhou, P. Angelov, An Approach to Autonomous Self-localization of a Mobile Robot in Completely Unknown Environment using Evolving Fuzzy Rule-based Classifier, Proc. 2007 IEEE International Conference on Computational Intelligence Applications for Defense and Security, April 1-5, 2007, Honolulu, Hawaii, USA, pp.131-138, IEEE Xplore.

  113. F. Klawonn, P. Angelov, Evolving Extended Naive Bayes Classifier, Proc. 6th IEEE International Conference on Data Mining (S. Tsumoto et al. Eds.), Los Alamitos, USA, 2006, ISBN 0769527027, pp. 643-647, IEEE Xplore.

  114. J. J. M. Hernandez, P. Angelov, X. Zhou, Soft Sensor for Predicting Crude Oil Distillation Side Streams using Takagi Sugeno Evolving Fuzzy Models, Proc. 2nd Annual Symposium on Nature Inspired Smart Adaptive Systems, 29 Nov. - 1 Dec. ,2006, Tenerife, Spain, ISBN 3-86130-926-2, pp.313-322, DOI:10.1.1.89.7041

  115. A. Evans, P. Angelov, X. Zhou, On-line Evolving Clustering of Web Documents, Proc. 2nd Annual Symposium on Nature Inspired Smart Adaptive Systems, 29 Nov.-1 Dec., 2006, Tenerife, Spain, ISBN 3-86130-926-2, pp.225-230.

  116. P. Angelov, Evolving Fuzzy Rule-based Systems for Modelling of Non-linear Non-stationary Processes, Proc. IFAC Workshop Energy Efficient Control, 2-5 Oct. 2006, Bansko, Bulgaria, pp.43-50.

  117. *P. Angelov, X. Zhou, Evolving Fuzzy Systems from Data Streams in Real-Time, Proc. 2006 International Symposium on Evolving Fuzzy Systems, 7-9 September, 2006, Ambleside, UK, IEEE Press, ISBN 0-7803-9719-3, pp.29-35.

  118. *E. Jones, P. Angelov, C. Xydeas, Recovery of LSP Coefficients in VoIP Systems using Evolving Takagi-Sugeno Fuzzy MIMO Models, Proc. 2006 International Symposium on Evolving Fuzzy Systems, 7-9 September, 2006, Ambleside, UK, IEEE Press, ISBN 0-7803-9719-3, pp. 208-214.

  119. *J. Macias, P. Angelov, X.-W. Zhou, Predicting Quality of the Crude Oil Distillation using Evolving Takagi-Sugeno Fuzzy Models, Proc. 2006 International Symposium on Evolving Fuzzy Systems, 7-9 Sept. 2006, Ambleside, UK, IEEE Press, ISBN 0-7803-9719-3, pp. 201-207.

  120. A. Memon, P. Angelov, H. Ahmed, An Approach to Real-Time Color-based Object Tracking, Proc. 2006 International Symposium on Evolving Fuzzy Systems, 7-9 September 2006, Ambleside, UK, IEEE Press, ISBN 0-7803-9719-3, pp.81-87.

  121. X.-W. Zhou, P. Angelov, Real-Time joint Landmark Recognition and Classifier Generation by an Evolving Fuzzy System, Proc. 2006 IEEE World Congress on Computational Intelligence, Vancouver, Canada, July 16-21, 2006, ISBN 0-7803-9489-5, pp.6314-6321.

  122. X.-W. Zhou, P. Angelov, G. Morris, Novelty Detection and Landmark Recognition by Real-time Evolving Clustering, Proc. UK Workshop on Computational Intelligence, UKCI2005, Essex, UK, 5-7 September, 2005, pp. 155-161.

  123. P. Angelov, E. Lughofer. P. E. Klement, Two Approaches for Data-Driven Design of Evolving Fuzzy Systems: eTS and FLEXFIS, Proc. The 2005 North American Fuzzy Information Processing Society Annual Conference, 21-25 June 2005, Ann Arbor, MI, USA, pp.31-35.

  124. P. Angelov, D. Filev, Simpl_eTS: A Simplified Method for Learning Evolving Takagi-Sugeno Fuzzy Models, Proc. The 2005 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Reno, USA, 22-25 May 2005, ISSN 0-7803-9158-6/05, pp.1068-1073.

  125. J. Victor, A. Dourado, P. Angelov, On-Line Construction and Rule Base Simplification by Replacement in Fuzzy Systems Applied to a Wastewater Treatment Plant, Proc. 16th IFAC World Congress, Prague, Czech Republic, July-2005, pp.1-6

  126. P. P. Angelov, N. Kasabov, Evolving Computational Intelligence Systems. Proc. 1st International Workshop on Genetic Fuzzy Systems, GFS-2005, Granada, Spain, April 2005, pp. 76-82.

  127. P. Angelov, Y. Zhang, and J. Wright. Automatic Design Generation of Component-based Systems using GA and Fuzzy Optimisation, Proc. 1st International Workshop, GFS-2005, Granada, Spain, April, pp. 95-100.

  128. P. Angelov, T. Evans, Semantic Categorization of Web-based Documents, Proc. 5th International Conf. on Recent Advances in Soft Computing, RASC2004, 16-18 Dec., Nottingham, UK, pp.500-505.

  129. P. Angelov, C. Xydeas, D. Filev, On-line Identification of MIMO Evolving Takagi-Sugeno Fuzzy Models, Proc. International Joint Conference on Neural Networks and International Conference on Fuzzy Systems, IJCNN-FUZZ-IEEE, Budapest, Hungary, 25-29 July, 2004, ISBN 0-7803-8354-0, pp. 55-60, IEEE Xplore.

  130. P. Angelov, J. Victor, A. Dourado, D. Filev, On-line evolution of Takagi-Sugeno Fuzzy Models, Proc. 2nd IFAC Workshop on Advanced Fuzzy/Neural Control, 16-17 Sept. 2004, Oulu, Finland, pp.67-72.

  131. P. Angelov, Y. Zhang, J. Wright, R. Buswell, V. Hanby, Automatic Design Synthesis and Optimization of Component-based Systems by Evolutionary Algorithms, In: Proc. Genetic and Evolutionary Computation Conference GECCO-2003, July 12-16, 2003, IL, USA, v. II, pp.1938-1950.

  132. P. Angelov, An Approach to On-line Design of Fuzzy Controllers with Evolving Structure, Proc. 4th International Conference on Recent Advances in Soft Computing, RASC-2002, Nottingham, 12-13 December 2002, pp. 55-56.

  133. P. Angelov, An Approach for Rule-base Adaptation using On-line Clustering, Proc. 2nd EUNITE Conference, 19-22 September 2002, Albufeira, Portugal, pp. 47-52.

  134. P. Angelov, D. Filev, Flexible Models with Evolving Structure, Proc. IEEE Symposium on Intelligent Systems, Varna, Bulgaria, 10-12 September 2002, v.2, pp.28-33.

  135. P. Angelov, R. Buswell, J. Wright, D. Loveday, Evolving Rule-based Control, Proc. EUNITE Symposium, 13-15 December 2001, Tenerife, Spain, pp.36-41.

  136. P. Angelov, R. Buswell, Evolving Rule-based Models: A Tool for Intelligent Adaptation, Proc. 9th IFSA World Congress, Vancouver, BC, Canada, 25-28 July 2001, pp.1062-1067.

  137. P. Angelov, R. Buswell, J.A. Wright, Transparency and Simplification of Rule-Based Models for On-line Adaptation, Proc. 2nd EUSFLAT Conference, Leicester, 5-7 Sept. 2001, pp. 234-237.

  138. P. P. Angelov, V.I. Hanby, R. A. Buswell and J.A. Wright, A Methodology for Modelling HVAC Components using Evolving Fuzzy Rules, Proc. IEEE International Conference on Industrial Engi-neering, Control and Instrumentation, IECON-2000, 22-28 Oct. 2000, Nagoya, Japan, pp. 247-252.

  139. P. P. Angelov, J.A. Wright, A Centre-of-Gravity-based Recombination Operator for Genetic Algorithms, Proc. IEEE International Conference on Industrial Engineering, Control and Instrumentation, 22-28 October 2000, Nagoya, Japan, pp. 259-264, IEEE Press.

  140. P. Angelov, Evolving Fuzzy Rule-Based Models, Proc. 8th IFSA World Congress, Taipei, Taiwan, August 17-20, 1999, v.1, pp.19-23.

  141. P. Angelov, A Fuzzy Approach to Building Thermal Systems Optimization, Proc. 8th IFSA World Congress, Taipei, Taiwan, August 17-20, 1999, v.2, pp.423-426.

  142. O. Bernard, G. Bastin and P. Angelov, Hybrid Modelling of Biotechnological Processes using Neural Networks, Proc. 14th World IFAC Congress, Beijing, July 1999, v. L, pp. 145-150.

  143. P. Angelov, Self-Learning of Fuzzy-Rule-based Models by GA, Proc. International Conference on Intelligent Control'98, Sofia, Bulgaria, 14-16 Oct. 1998, ISBN 954-9641-05-8 (T2), pp. 46-49.

  144. P. Angelov, D. Lakov, Fuzzy Rule-based System for Risk Assessment, Proc. International Conference on Intelligent Control'98, Sofia, Bulgaria, 14-16 Oct. 1998, ISBN 954-9641-05-8 (T2), pp. 42-45.

  145. P. Angelov, R. Guthke, R. Berkholz, Optimal Control of a Fermentation Process using Neural Networks and Genetic Algorithms, Proc. 6th European Congress on Soft Computing and Intelligent Technologies, EUFIT'98, Aachen, Germany, Sept. 7-10, 1998, v.3, pp.1591-1595.

  146. K.-H. Bellgardt, S. Tzonkov, R. Nenov and P. Angelov, Future Prospects and Trends in Modeling, Control and Measurements in Biotechnology, Proc. 10th International Workshop Bioprocess Systems'97, Sofia, Bulgaria, 14-16 October, 1997, pp. I.1-I.11.

  147. P. Angelov, Intelligent Optimal Control of Biotechnological Processes, Proc. 4th European Congress on Intelligent Techniques and Soft Computing, EUFIT'96, Aachen, Germany, 2-5 September 1996, v.2, pp.1033-1037.

  148. P. Angelov, R. Guthke, An Approach to Fuzzy Optimal Control supported by Genetic Algorithms, Proc. International Panel Conference on Soft Computing, Budapest, Hungary, 7-10 October, 1996, pp. 11-17.

  149. P. Angelov, Fuzzy Optimal Control based on Genetic Algorithms, Proc. 2nd International Conference FUBEST'96, Sofia, Bulgaria, 9-11 Oct., 1996, pp.57-60.

  150. P. Angelov, Intelligent Optimal Control of Biotechnological Processes, Proc. 16th Internatio-nal Conference Information Technology Interfaces, Pula, Croatia, 18-21 June 1996, pp.353-358

  151. A. Gegov, P. Koprinkova and P. Angelov, Hierarchical Fuzzy Control of Traffic Networks, Proc. International Panel Conference on Soft Computing, Budapest, Hungary, 7-10 October, 1996, pp. 107-112.

  152. P. Angelov, M. Petrov, S. Tzonkov, An Approach to Optimal Control of Biotechnological Processes Based on Soft Computing, Proc. International Conference on Automatics & Informatics, Sofia, Bulgaria, 9-11 October, 1996, pp.252-255.

  153. P. Angelov, An Method for Fuzzy Linear Dynamic Programing, Proc. 3rd European Congress on Intelligent Technologies and Soft Computing, EUFIT'95, Aachen, Germany, August 28-31 1995, v.2, pp. 1294-1298.

  154. P. Angelov, Application of Intuitionistic Fuzzy Sets to Optimization Problems, Proc. 13th Symposium on Mathematical Methods in Economics, 18-20 September 1995, Ostrava, Czech Republic, pp. 1-8.

  155. P. Angelov, An Approach to Optimisation of Biotechnological Processes based on Neural Networks, Proc. 17th International Conference Information Technology Interfaces, Pula, Croatia, 13-16 June 1995, pp. 401-406.

  156. P. Angelov, S. Tzonkov, Application of Soft Computing in Bioprocess Engineering, Proc. International Workshop Bioprocess Engineering'95, Sofia, Bulgaria, 2-5 Oct., 1995, pp. iv-ix.

  157. P. Angelov, Neural-Network based Modeling and Optimization of Whey Fermentation, Proc. International Conference on Automatics and Informatics, Sofia, Bulgaria, 7-10 November, 1995, pp. 414-417.

  158. P. Angelov, A new Method for Solving Linear Programming Problems with Fuzzy Parameters, Proc. 2nd Euro Congress on Intelligent Techniques and Soft Computing, EUFIT'94, Aachen, Germany, 20-23 September, 1994, v.2, pp.962-966.

  159. P. Angelov, M. Petrov and S. Tzonkov, An Approach for Training a type of Fuzzy Neural Networks as Fuzzy Optimization, Proc. 10th International Conference on Systems Engineering, Coventry, UK, 6-8 September, 1994, pp. 47-51.

  160. P. Angelov, Analytical Approach for Solving a Type of Fuzzy Optimization Problems, Proc. International Workshop on Fuzzy Based Expert Systems, FUBEST'94, 28-30 September, 1994, Sofia, Bulgaria, pp.11-14.

  161. P. Angelov, A Parameterized Generalization of Fuzzy Mathematical Programming Problem, Proc. 5th IFSA World Congress, Seoul, Korea, July 4-9, 1993, v.1, pp.612-615.

  162. P. Angelov, An Analytical Approach for FMP Problem Solving and its Application to Neural Networks Learning, Proc. 1st European Congress on Fuzzy and Intelligent Techniques, EUFIT'93, Aachen, Germany, 7-10 September, 1993, v.3, pp.1255-1266.

  163. P. Angelov, L. Kuncheva, About Analytical Solving Fuzzy Mathematical Programming Problem, Proc. International Conference on Mathematical Modelling and Computing'93 (S. Markov Ed.), Sozopol, Bulgaria, 14-17 September 1993, pp.109-112.

  164. P. Angelov, An Analytical Solution of Fuzzy Mathematical Programming Problem, Proc. 2nd Balkan Conference on Operations Research, Thessaloniki, Greece, 18-21 Oct 1993, pp.605-610

  165. Kuncheva, P. Angelov, A Combined Iterative-Analytical Training of a Counter-propagation Fuzzy Neural Network, Proc. 2nd Balkan Conference on Operations Research, Thessaloniki, Greece, 18-21 October, 1993, pp. 780-783.

  166. P. Angelov, M. Petrova and S. Tzonkov, A Fuzzy Approach to Optimization of Biotechnological Process Condition, Proc. 2nd Balkan Conference on Operations Research, Thessaloniki, Greece, 18-21 October, 1993, pp.896-903.

  167. P. Angelov, Fuzzy Optimal Control of Ethanol Synthesis, Proc. 2nd International Conference of BUFSA, Trabzon, Turkey, 31 August-1 September 1992, pp.119-122.

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