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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 (132):

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  1. A. Aghasanli, P. Angelov, D. Kangin, J. Kerns, R. F. Shepherd, Transfer learning from inorganic materials to ivory detection, Nature Scientific Reports, accepted 15 April 2025.

  2. R. Vyas, B. Williams, H. Rahmani, R. Boswell-Challand, Z. Jiang, P. Angelov, S. Black, Demonstrable and anatomy-driven knuckle identification via crease map segmentation, Signal Image and Video Processing, 19 (4): 1-11, article 318, 21 February 2025,

  3. D. Kangin, P. Angelov, Z. Zhang, IDEAL: Interpretable-by-Design ALgorithms for learning from foundation feature spaces, Neurocomputing (IF 5.779), v. 626, 14 April 2025, DOI: 10.1016/j.neucom.2025.129464

  4. Y. Li, P. Angelov, N. Suri, Adversarial attack detection via fuzzy predictions, IEEE Transactions on Fuzzy Systems, (IF 12.253), 32(12),7015-7024,Oct 2024, DOI: 10.1109/TFUZZ.2024.3473768

  5. Y. Zhu, A. Bouridane, M. E. Celebi, D. Konar, P. Angelov, Q. Ni, R. Jiang, Quantum Face Recognition with Multi-Gate Quantum Convolutional Neural Network, IEEE Transactions on AI, 28 June 2024, DOI: 10.1109/TAI.2024.3419077

  6. E. Soares, P. Angelov, Z. Zhang, An Explainable approach to Deep Learning from CT-scans for Covid Identification, Evolving Systems (IF 2.8), 2024, 15 (6), 2159-2168, DOI: 10.1007/s12530-024-09608-2

  7. X. Gu, P. Angelov, Q. Shen, Semi-supervised Fuzzily Weighted Adaptive Boosting for Classification, IEEE Transactions on Fuzzy Systems (IF 12.253), 32(4): 2318-2330, April 2024, DOI: 10.1109/TFUZZ.2024.3349637.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. X. Gu, J. Han, Q. Shen, P. Angelov, Autonomous Learning for Fuzzy Systems: a review, Artificial Intelligence Review (IF 9.588), 56:7549-7595, 2023, DOI: 10.1007/s10462-022-10355-6, published 15 Dec. 2022.

  13. 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.

  14. 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).

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. X. Gu, P. Angelov, Q. Shen, Self-Organizing Fuzzy Belief Inference System for Classification, IEEE Transactions on Fuzzy Systems (IF 12.253), 30(12): 5473-5483, May 2022, DOI: 10.1109/ TFUZZ.2022.3179148.

  20. N. I. Arnold, P. Angelov, P. M. Atkinson, An Improved eXplainable Point Cloud Classifier (XPCC), IEEE Transactions on AI, 4(1): 71-80, Feb. 2022, DOI: 10.1109/TAI.2022.3150647

  21. 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

  22. 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), 14: 828-851, Jan. 2022, DOI: 10.1007/s12559-021-09945-3.

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

  24. 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), 30(7): 2649-2664, Jul 2022, DOI: 10.1109/TFUZZ.2021.3090898.

  25. 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.

  26. 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.

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

  28. 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: 10.1016/j.engappai.2020.103559.

  29. 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.

  30. 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.

  31. 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.

  32. 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.

  33. 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.

  34. 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.

  35. 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.

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

  37. 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.

  38. 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

  39. 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.

  40. 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.

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

  42. 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

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

  44. 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.

  45. 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.

  46. 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.

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

  48. 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.

  49. 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.

  50. † 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.

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

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

  53. 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.

  54. 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.

  55. 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.

  56. † 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.

  57. 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

  58. 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.

  59. 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.

  60. 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.

  61. 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.

  62. 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

  63. 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.

  64. 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

  65. 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.

  66. † N. Harris, L. Carpenter, J. Lee, G. Vaughan, M. Filus, R. Jones, B. OuYang, J. Pyle,  A. Robinson, 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.

  67. 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.

  68. 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.

  69. 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.

  70. 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.

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

  72. 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.

  73. 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.

  74. 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.

  75. 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.

  76. 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.

  77. † 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.

  78. † 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.

  79. 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.

  80. 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

  81. 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

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

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

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

  85. 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.

  86. 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.

  87. 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.

  88. † 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.

  89. 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.

  90. 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.

  91. † 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.

  92. 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.

  93. † 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.

  94. 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.

  95. 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.

  96. 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.

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

  98. † 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.

  99. † 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.

  100. 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.

  101. 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.

  102. 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.

  103. *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

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

  105. 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

  106. 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.

  107. 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.

  108. 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.

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

  110. 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.

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

  112. 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.

  113. 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.

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

  115. 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.

  116. 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.

  117. 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.

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

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

  120. 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.

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

  122. 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.

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

  124. 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.

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

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

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

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

  129. 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.

  130. 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.

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

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

Lancaster University

© 2015 by Plamen Angelov

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