top of page

The list of all peer reviewed conference publications (the list continues from the List of all publications):

​​

E. Peer reviewed Conference publications (179)

​​​

  1. J. P. Klock, J. P. Pinto, J. Moura, Y. Li, C. Castro, P. Angelov, Vision-based Landing Guidance through Tracking and Orientation Estimation, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV - 2025), March 2025, Tucson, AZ, USA

  2. Y. Li, Y. Sun, P. Angelov, Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement, The 39th AAAI Conference on AI, Philadelphia, PA, USA, 27 Feb – 2 March 2025.

  3. Y. Li, P. Angelov, Explainable Audio-Visual Representation Learning via Prototypical Contrastive Masked Autoencoder, Advances in Neural Information Processing Systems, NeurIPS – 2024, 5th Workshop on Self-supervised Learning: Theory and Practice, https://openreview.net/pdf?id=ZLPVS0T4lc

  4. Y. Li, P. Angelov, N. Suri, Robust Self-Supervised Learning for Adversarial Attack Detection, Advances in Neural Information Processing Systems, NeurIPS – 2024, 5th Workshop on Self-supervised Learning: Theory and Practice, https://openreview.net/pdf?id=VSYnG9s2mo

  5. Y. Li, P. Angelov, Z. Yu, A. Lopez Pellicer, N. Suri, Federated adversarial learning for robust autonomous landing runway detection, International Conference on Artificial Neural Networks, In: Proc. 33rd ICANN Lugano, Switzerland, September 17-20, 2024, Proceedings, Part VI, 159-173, DOI: 10.1007/978-3-031-72347-6_11

  6. Y. Li, P. Angelov, N. Suri, Self-supervised representation learning for adversarial attack detection, European Conference on Computer Vision (ECCV), 18th Conference, Milano, Italy, Sept 29 – Oct 4, 2024, Proceedings, Part LX , DOI: 10.1007/978-3-031-73027-6_14, 236-252

  7. A. Lopez Pellicer, P. Angelov, S. Neeraj, UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification, IEEE World Congress on Computational Intelligence, Yokohama, Japan, 1-5 July 2024, DOI: 10.1109/IJCNN60899.2024.10651159

  8. Y. Li, P. Angelov, S. Neeraj, Rethinking Self-supervised Learning for Cross-domain Adversarial Sample Recovery, IEEE World Congress on Computational Intelligence (IEEE WCCI 2024) Yokohama, Japan, 1-5 July 2024, DOI: 10.1109/IJCNN60899.2024.10650687

  9. A. Lopez Pellicer, Y. Li, P. Angelov, PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection, CVPR-W, 2024, pp. 3809-3817, DOI: 10.1109/CVPRW63382.2024.00385

  10. D. Kangin, P. Angelov, Unsupervised Domain Adaptation within Deep Foundation Latent Spaces, ICLR-W, 2024.

  11. A. Aghasanli, P. Angelov, Edge Implementation of Unsupervised Self-evolving Vision Classifier, IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS-2024, Madrid, Spain, 23-24 May 2024, DOI: 10.1109/EAIS58494.2024.10570024

  12. B. Tomczyk, P. Angelov, D. Kangin, Machine Learning within Latent spaces formed by Foundation Models, 12th IEEE International Conference on Intelligent Systems, IS’24, Varna, Bulgaria, 29-31 August 2024, DOI: 10.1109/IS61756.2024.10705264

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. N. L. Baisa, B. Williams, H. Rahmani, P. Angelov, S. Black, Hand-based person identification using global and part-aware deep feature representation learning, 2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 19-22 April 2022, DOI 10.1109/IPTA54936.2022.9784133.

  21. 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.

  22. 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.

  23. 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.

  24. 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 within 2021 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021), Orlando, FL USA, 3-7 Dec. 2021, DOI: 10.110/SSCI50451.2021.9659850, published online at IEEE Xplore on 24 January 2022.

  25.  R. Vyas, H. Rahmani, R Boswell-Challand, P. Angelov, S Black, Bryan 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.

  26. 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.

  27. 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, DOI: 10.1109/SMC42975.2020. 9282812.

  28. 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, DOI: 10.1109/FUZZ 48607.2020.9177557.

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

  30. 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.

  31. 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.

  32. 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.  

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

  34. 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, Granada, Spain, pp. 441-446. 

  35. 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.

  36. 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.

  37. 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.

  38. 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.

  39. 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.

  40. X. Gu, P. Angelov, A Deep Rule-based Approach for Satellite Scene Image Analysis, IEEE Intern. Conf. on Systems, Man and Cybernetics, IEEE SMC2018, Miyazaki, Japan, 7-10 Oct 2018, pp.2778-2783.

  41. 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.

  42. 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.

  43. 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.

  44. 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.

  45. 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.

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

  47. 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.

  48. † 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.

  49. 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.

  50. 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.

  51. *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.

  52. 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.

  53. 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.

  54. 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.

  55. 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.

  56. 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.

  57. 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.   

  58. 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.

  59. 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.

  60. 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.

  61. 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.

  62. 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.

  63. 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.

  64. 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.

  65. 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.

  66. 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.

  67. 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.

  68. 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.

  69. 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.

  70. 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.

  71. 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.

  72. 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.

  73. 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.

  74. 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.

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

  76. 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.

  77. 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.

  78. 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.

  79. 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.

  80. 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.

  81. 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.

  82. M. Suvorov, S. Iliev, 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.

  83. *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.

  84. 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.

  85. 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.

  86. 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.

  87. 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).

  88. 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.

  89. 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.

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

  91. 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.

  92. 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.

  93. 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.

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

  95. 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.

  96. 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.

  97. 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

  98. 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.

  99. 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.

  100. 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.

  101. 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.

  102. 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.

  103. 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.

  104. 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.

  105. 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.

  106. 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.

  107. 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.

  108. 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.

  109. 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.

  110. *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.

  111. 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.

  112. 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.

  113. 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.

  114. 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.

  115. 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.

  116. 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.

  117. 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.

  118. 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.

  119. 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.

  120. 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.

  121. 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.

  122. 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.

  123. 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.

  124. 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.

  125. 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.

  126. 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

  127. 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.

  128. 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.

  129. *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.

  130. *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.

  131. *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.

  132. 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.

  133. 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.

  134. 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.

  135. 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.

  136. 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.

  137. 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

  138. 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.

  139. 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.

  140. 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.

  141. 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.

  142. 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.

  143. 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.

  144. 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.

  145. 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.

  146. 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.

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

  148. 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.

  149. 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.

  150. 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 Eng. Control and Instrumentation, IECON-2000, 22-28 Oct 2000, Nagoya, Japan, pp. 247-252.

  151. 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.

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

  153. 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.

  154. 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.

  155. 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.

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

  157. 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.

  158. 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.

  159. 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.

  160. 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.

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

  162. 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

  163. A. Gegov, P. Koprinkova and P. Angelov, Hierarchical Fuzzy Control of Traffic Networks, Proc. Internat. Panel Conf. on Soft Computing, Budapest, Hungary, 7-10 Oct., 1996, pp. 107-112.

  164. 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.

  165. 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.

  166. 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.

  167. 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.

  168. 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.

  169. P. Angelov, Neural-Network based Modeling and Optimization of Whey Fermentation, Proc. Internat. Conf. on Automatics and Informatics, Sofia, Bulgaria, 7-10 Nov. 1995, pp. 414-417.

  170. 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.

  171. 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.

  172. 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.

  173. 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.

  174. 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.

  175. 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.

  176. 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

  177. 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.

  178. 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.

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

Lancaster University

© 2015 by Plamen Angelov

  • LinkedIn Clean Grey
bottom of page