Selected Publications (in order of my preference)

Books (top 3)

• P.P. Angelov, Evolving Rule-based Models: A Tool for Design of Flexible Adaptive Systems, Springer-Verlag, Heidelberg, New York, 2002, ISBN 3-7908-1457-1
• P. Angelov, D. Filev and N. Kasabov (Eds.), Evolving Intelligent Systems: Methodology and Applications, 484pp., John Willey and Sons, IEEE Press Series on Computational Intelligence, Feb. 2010, ISBN: 978-0-470-28719-4
• P. Angelov, D. Filev, N. Kasabov, O. Cordon (Eds.), Evolving Fuzzy Systems, Procedings of the 2006 International Symposium on Evolving Fuzzy Systems EFS'06, 372pp., IEEE Press, 2006, ISBN 0-7803-9718-5.

Journal papers (top 20):

1. 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, vol.34, No1, 2004, pp.484-498. ISSN 1094-6977
2. P. Angelov, R. Buswell, Identification of Evolving Rule-based Models, IEEE Transactions on Fuzzy Systems, ISSN 1063-6706, vol. 10, No5, pp. 667-677, 2002
3. P. Angelov, X. Zhou, Evolving Fuzzy-Rule-based Classifiers from Data Streams, IEEE Transactions on Fuzzy Systems, ISSN 1063-6706, special issue on Evolving Fuzzy Systems, December 2008, vol. 16, No6, pp.1462-1475
4. P. Angelov, A. Kordon, Adaptive Inferential Sensors based on Evolving Fuzzy Models: An Industrial Case Study, IEEE Transactions on Systems, Man and Cybernetics - part B, 2010, DOI: 10.1109/TSMCB.2009.2028315, vol. 40 (2), pp.529-539
5. J. Trevisan, P.P. Angelov, F.L.A. Martin, Derivation of a computational approach to iteratively discriminate a transformation phenotype in Syrian hamster embryo (SHE) cells, Mutagenesis, vol. 24,  is. 6, pp. 543-543, Nov. 2009, impact factor 3.16
6. P. Angelov, X. Zhou, Evolving Fuzzy-Rule-based Classifiers from Data Streams, IEEE Transactions on Fuzzy Systems, ISSN 1063-6706, special issue on Evolving Fuzzy Systems, December 2008, vol. 16, No6, pp.1462-1475
8. P. Angelov, E. Lughofer and X. Zhou, Evolving Fuzzy Classifiers with Different Architectures, Fuzzy Sets and Systems, vol. 159, pp.3160-3182, 2008
9. 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, ISSN 0974-1259, special issue on the future of fuzzy systems research, vol.4, No.4, pp. 392-401, December 2008*
10. L. Chen, O. Bernard, G. Bastin and P.Angelov, Hybrid Modelling of Biotechnological Processes using Neural Networks, Control Engineering Practice, vol.8, No7, pp.821-827, 2000
11. P. Angelov, R. Guthke, A GA-based Approach to Optimization of Bioprocesses Described by Fuzzy Rules, Journal of Bioprocess Engineering, vol.16, pp.299-301, 1997
12. P. Angelov, R. Buswell, Automatic Generation of Fuzzy Rule-based Models from Data by Genetic Algorithms, Information Sciences, ISSN 0020-0255, vol.150, No1/2, pp.17-31, 2003
13. P. Angelov, Supplementary Crossover Operator for Genetic Algorithms based on the Centre-of-Gravity Paradigm, Control and Cybernetics, vol. 30, No2, pp. 159-176, 2001
14. P.P. Angelov, A Fuzzy Controller with Evolving Structure, Information Sciences, ISSN 0020-0255, vol.161, pp.21-35, 2004
15. P. Angelov, An Approach for Fuzzy Rule-base Adaptation using On-line Clustering, International Journal of Approximate Reasoning, vol. 35 , No 3, pp. 275-289, March 2004
16. 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, vol.14, No.1, pp.33-55, January 2008
17. P. Angelov, Evolving Fuzzy Rule-based Models, Journal of Chinese Institute of Industrial Engineers, Taiwan, special issue on Soft Computing Applications to Industrial Engineering, ISSN 1017-0669, vol.17, pp. 459-468, 2000
18. D. Filev, P. Angelov, Fuzzy Optimal Control, Fuzzy Sets and Systems, vol.47, No2, 1992, pp.151-156, 1992
19. P. Angelov, An Analytical Method for Solving a Type of Fuzzy Optimization Problems, Control and Cybernetics, vol. 24, No3, pp. 363-373, 1995
20. P. Angelov, S. Tzonkov, Optimal Control of Biotechnological Processes Described by Fuzzy Sets , Journal of Process Control, vol.3, No3, pp.147-152, 1993

    Patent

    P. Angelov, Machine Learning (Collaborative Systems) patent (WO2008053161, priority date: 1 November 2006; international filing date 23 October 2007)

    Chapters in books (top 4)

1. P. Angelov, Evolving Takagi-Sugeno Fuzzy Systems from Data Streams (eTS+), In Evolving Intelligent Systems: Methodology and Applications (Angelov P., D. Filev, N. Kasabov Eds.), John Willey and Sons, IEEE Press Series on Computational Intelligence, ISBN: 978-0-470-28719-4, Feb. 2010
2. P. Angelov, Evolving Fuzzy Systems, In Encyclopedia on Complexity and System Science (Bob Meyers Editor-in-Chief), 10398 pp., ISBN: 978-0-387-75888-6, article 194, Springer, June 2009
3. P. Angelov, X.-W. Zhou, Evolving Fuzzy Classifier for Real-time Novelty Detection and Landmark Recognition by a Mobile Robot , In Mobile Robots: The Evolutionary Approach (N. Nedja, L. Coelho , L. Mourelle Eds.), Studies in Computational Intelligence Series, Springer, pp.95-124, ISBN 978-3-540-49719-6, March 2007
4. D. Filev, P. Angelov, Algortihms for Real-Time Clustering and Generation of Rules from Data, In: J. V. de Oliveira and W. Pedrycz (Eds.) Advances in Fuzzy Clustering and Its Applications, ISBN 978-0-470-02760-8, John Wiley and Sons, New York, USA, pp.353-370, 2007

Peer reviewed papers in proceedings of international conferences (top 30)

* best paper award


1. 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, England, UK, IEEE Press, pp.349-354.
2. J Andreu, P. Angelov, Real-Time Recognition from Wireless Sensors Using Evolving Fuzzy Systems, 2010 IEEE World Congress on Computational Intelligence,18-23 July 2010, Barcelona, Catalunya, Spain, pp.2652-2659, ISBN 978-1-4244-6920-8.
3. 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: E. H¨ullermeier, R. Kruse, and F. Hoffmann (Eds.): IPMU 2010, Part II, CCIS 81, pp. 30–43, 2010, ISBN 3-642-14057-2 Springer Berlin Heidelberg NewYork, ISSN 1865-0929.
4. J. A. Iglesias, P. Angelov, A. Ledezema, A. Sanchis,User Modeling: Through Statistical Analysis and an Evolving Classifier, 2010 IEEE World Congress on Computational Intelligence,18-23 July 2010, Barcelona, Catalunya, Spain, pp. 3226-3233, ISBN 978-1-4244-6920-8.
5. P. Angelov, C. Xydeas, D. Filev, On-line Identification of MIMO Evolving Takagi-Sugeno Fuzzy Models, International Joint Conference on Neural Networks and International Conference on Fuzzy Systems, IJCNN-FUZZ-IEEE, Budapest, Hungary, 25-29 July, 2004, 55-60, ISBN 0-7803-8354-0
6. P. Angelov, D. Filev, Simpl_eTS: A Simplified Method for Learning Evolving Takagi-Sugeno Fuzzy Models,The 2005 IEEE International Conference on Fuzzy Systems FUZZ-IEEE, Reno, Las vegas, USA, 22-25 May 2005, pp.1068-1073, ISSN 0-7803-9158-6/05
7. P. Angelov, R. Buswell, Evolving Rule-based Models: A Tool for Intelligent Adaptation, 9th IFSA World Congress, Vancouver, BC, Canada, 25-28 July 2001, pp.1062-1067
8. P. Angelov, J. Victor, A. Dourado, D. Filev, On-line evolution of Takagi-Sugeno Fuzzy Models, Proc. Of the 2nd IFAC Workshop on Advanced Fuzzy/Neural Control, 16-17 September 2004, Oulu, Finland, pp.67-72
9. J. A. Iglesias, P. Angelov, A. Ledezema, A. Sanchis, Modelling Evolving User Behaviours, 2009 IEEE Symposium Series on Computational Intelligence, 2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems, 29 March-2 April, 2009, Sheraton Music City Hotel, Nashville, TN, USA, Proceedings, IEEE Press, ISBN: 978-1-4244-2754-3, pp.16-23*
10. P. Angelov, X. Zhou, On Line Learning Fuzzy Rule-based System Structure from Data Streams, 2008 IEEE International Conference on Fuzzy Systems within the IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6, 2008, pp.915-922, ISBN 978-1-4244-1821-3/08.
11. P. Angelov, X. Zhou, Evolving Fuzzy Systems from Data Streams in Real-Time, 2006 International Symposium on Evolving Fuzzy Systems, 7-9 September, 2006, Ambelside, Lake District, UK, IEEE Press, pp.29-35, ISBN 0-7803-9719-3 *
12. P. Angelov, R. Ramezani,X. Zhou, Autonomus Novelty Detection and Object Tracking in Video Streams using Evolving Clustering and Takagi-Sugeno type Neuro-Fuzzy System, 2008 IEEE International Joint Conference on Neural Networks within the IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6, 2008, pp.1457-1464, ISBN 978-1-4244-1821-3/08
13. R. Ramezani, P. Angelov, X. Zhou, A Fast Approach to Novelty Detection in Video Streams using Recursive Density Estimation, 4th International IEEE Symposium on Intelligent Systems, 6-8 September, 2008, Varna, Bulgaria, v.II, pp.14-2 -- 14-7, ISBN 978-1-4244-1739-1/08.
14. P. Angelov, A. Kordon, X. Zhou, Evolving Fuzzy Inferential Sensors for Process Industry, 3rd International Workshop on Genetic and Evolving Fuzzy Systems, 4-7 March, 2008, Witten-Bomerholz, Germany, pp. 41-46, ISBN 978-1-4244-1613-4.
15. 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, 2008 UKSIM: 10th International Conference on Computer Modelling and Simulation, 1-3 April 2008, Emanuel College, Cambridge, UK, pp.64-69.
16. P. Angelov, X. Zhou, F. Klawonn, Evolving Fuzzy Rule-based Classifiers, First 2007 IEEE International Conference on Computational Intelligence Applications for Signal and Image Processing, April 1-5, 2007, Honolulu, Hawaii, USA, pp.220-225.
17. X. Zhou, P. Angelov, An Approach to Autonomous Self-localization of a Mobile Robot in Completely Unknown Environment using Evolving Fuzzy Rule-based Classifier, First 2007 IEEE International Conference on Computational Intelligence Applications for Defense and Security, April 1-5, 2007, Honolulu, Hawaii, USA, pp.131-138.
18. E. Lughofer, P. Angelov, Detecting and Responding to Drift and Shift in On-line Data Streams with Evolving Fuzzy Systems, 2009 IFSA World Congress and 2009 EUSFLAT Conference, 19-23 July 2009, Lisbon, Portugal, pp.931-937, ISBN 978-95079-6-8
19. 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, 7-10 October, 2007, Montreal, Canada, ISBN 1-4244-0991-8/07, pp.2050-2055.
20. A. Evans, P. Angelov and X. Zhou, On-line Evolving Clustering of Web Documents, 2nd Annual Symposium on Nature Inspired Smart Adaptive Systems, 29, Nov-1, Dec, 2006, Tenerife, Spain, pp.225-230, ISBN 3-86130-926-2.
21. J. Macias, P. Angelov and X.-W. Zhou, Predicting Quality of the Crude Oil Distillation using Evolving Takagi-Sugeno Fuzzy Models, In Proc. 2006 International Symposium on Evolving Fuzzy Systems, 7-9 September, 2006, Ambelside, Lake District, UK, IEEE Press, pp. 201-207, ISBN 0-7803-9719-3*
22. X.-W. Zhou, P. Angelov, Real-Time joint Landmark Recognition and Classifier Generation by an Evolving Fuzzy System, 2006 IEEE World Congress on Computational Intelligence, Vancouver, BC, Canada, July 16-21, 2006, pp.6314-6321, ISBN 0-7803-9489-5 (received a student travel grant from IEEE).
23. P. Angelov, Y. Zhang, J. Wright, R. Buswell, V. Hanby, Automatic Design Synthesis and Optimization of Component-based Systems by Evolutionary Algorithms, In: Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2003, July 12-16, 2003, IL, USA, vol. II, pp.1938-1950 *
24. P.P. Angelov, J.A. Wright, A Centre-of-Gravity-based Recombination Operator for Genetic Algorithms, IEEE International conference on Industrial Engineering, Control and Instrumentation IECON-2000, 22-28 October 2000, Nagoya, Japan, pp. 259-264
25. P. Angelov, Evolving Fuzzy Rule-Based Models, Proc. 8th IFSA World Congress, Taipei, Taiwan, August 17-20, 1999, vol.1, pp.19-23
26. O. Bernard, G. Bastin and P. Angelov, Hybrid Modelling of Biotechnological Processes using Neural Networks, Proc. 14th World IFAC Congress, Beijing, July 1999, vol.L, pp. 145-150
27. P. Angelov, Self-Learning of Fuzzy-Rule-based Models by GA, Proc. Conference on Intelligent Control'98, Sofia, Bulgaria, 14-16 Oct. 1998, pp. 46-49, ISBN 954-9641-05-8 (T2)
28. P. Angelov, R. Guthke, An Approach to Fuzzy Optimal Control supported by Genetic Algorithms, Proc. International Panel Conference on Soft Computing, Budapest, Hungary, Oct. 7-10, 1996, pp. 11-17
29. P. Angelov, A Parameterized Generalization of Fuzzy Mathematical Programming Problem, 5th IFSA World Congress, Seoul, Korea, July 4-9, 1993, vol.1, pp.612-615
30. P. Angelov, L. Kuncheva, About Analytical Solving Fuzzy Mathematical Programming Problem, Proc. Intern. Conf. on Math. Modelling and Comp.'93 (S. Markov Ed.), Sozopol, Bulgaria, 14-17 Sept. 1993, pp.109-112

Papers at International Conferences published as abstracts only (top 2)

1. P. Angelov, C. Xydeas, C. D. Bocaniala, D. Ansell, C. Patchett and M. Everett, UAV collision avoidance - state of the art and possible solutions, VTOL UAV, Helitech, 3-5 Oct. 2007, Duxford, UK.
2. P. Angelov, F. von Eggeling, R. Guthke, Classification of Carcinoma Kidney Tissue Status based on the Data of Protein Expression using LS – SVM, International Workshop on Intelligent Technologies for Gene Expression-based Individualized Medicine, Jena, Germany, 9 May 2003, pp. 18-19, full paper on CD-ROM

Technical reports (top 4)

1. P. Angelov Passive Optimal 'Sense and Avoid' Re-routeing (POSAR): An Integrated Approach to Autonomous Collision Detection, Avoidance, and Re-routeing of Uninhabited Aerial Systems, 27pp., 16 May 2008.
2. P.P. Angelov, C. D. Bocaniala and C. Xydeas, UAV Collision Avoidance Algorithm Development - Final Report, issue 3, 27 March 2007, Lancaster, 69pp.
3. M. Everett, P. Angelov, EvoMap: On-Chip Implementation of Intelligent Information Modelling using EVOlving MAPping, 2005, Lancaster University, Lancaster, UK, 15pp.
4. P.P. Angelov, V. I. Hanby and J. A. Wright, Automatic Generation of Secondary HVAC Systems Configuration, Report on ASHARE-1049 RP, June 2000, Loughborough, 45pp.