Plamen P Angelov
Plamen P Angelov
Chair Professor in Intelligent Systems, School of Computing and Communications, Lancaster University
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Cited by
Cited by
An approach to online identification of Takagi-Sugeno fuzzy models
PP Angelov, DP Filev
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34 …, 2004
SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification
E Soares, P Angelov, S Biaso, MH Froes, DK Abe
MedRxiv, 2020.04. 24.20078584, 2020
Explainable artificial intelligence: an analytical review
PP Angelov, EA Soares, R Jiang, NI Arnold, PM Atkinson
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 11 (5 …, 2021
Evolving fuzzy-rule-based classifiers from data streams
PP Angelov, X Zhou
Ieee transactions on fuzzy systems 16 (6), 1462-1475, 2008
Optimization in an intuitionistic fuzzy environment
PP Angelov
Fuzzy sets and Systems 86 (3), 299-306, 1997
Evolving intelligent systems: methodology and applications
P Angelov, DP Filev, N Kasabov
John Wiley & Sons, 2010
Evolving rule-based models: a tool for design of flexible adaptive systems
PP Angelov
Springer Science & Business Media, 2002
Simpl_eTS: A simplified method for learning evolving Takagi-Sugeno fuzzy models
P Angelov, D Filev
The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ'05 …, 2005
Towards explainable deep neural networks (xDNN)
P Angelov, E Soares
Neural Networks 130, 185-194, 2020
Autonomous learning systems: from data streams to knowledge in real-time
P Angelov
John Wiley & Sons, 2012
Evolving fuzzy systems from Data Streams in Real-time
P Angelov, X Zhou
2006 International Symposium on Evolving Fuzzy Systems, 29-35, 2006
Evolving Fuzzy Systems from Data Streams in Real-time
P Angelov, X Zhou
International Symposium on Evolving Fuzzy Systems, 29-35, 2006
PANFIS: A novel incremental learning machine
M Pratama, SG Anavatti, PP Angelov, E Lughofer
IEEE Transactions on Neural Networks and Learning Systems 25 (1), 55-68, 2013
Extracting biological information with computational analysis of Fourier-transform infrared (FTIR) biospectroscopy datasets: current practices to future perspectives
J Trevisan, PP Angelov, PL Carmichael, AD Scott, FL Martin
Analyst 137 (14), 3202-3215, 2012
Evolving takagi-sugeno fuzzy systems from streaming data (eTS+)
P Angelov
Evolving intelligent systems: methodology and applications 12, 21, 2010
Evolving fuzzy classifiers using different model architectures
P Angelov, E Lughofer, X Zhou
Fuzzy sets and systems 159 (23), 3160-3182, 2008
A new type of simplified fuzzy rule-based system
P Angelov, R Yager
International Journal of General Systems 41 (2), 163-185, 2012
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
E Lughofer, P Angelov
Applied Soft Computing 11 (2), 2057-2068, 2011
An approach for fuzzy rule-base adaptation using on-line clustering
P Angelov
International Journal of Approximate Reasoning 35 (3), 275-289, 2004
An overview on fault diagnosis and nature-inspired optimal control of industrial process applications
RE Precup, P Angelov, BSJ Costa, M Sayed-Mouchaweh
Computers in Industry 74, 75-94, 2015
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