P. Angelov

发表

On-Line Evolution of Takagi-Sugeno Fuzzy Models

Dimitar Filev, P. Angelov, J. Victor, 2004, IFAC Proceedings Volumes.

On line learning fuzzy rule-based system structure from data streams

Plamen P. Angelov, Xiaowei Zhou, P. Angelov, 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

Evolving Fuzzy Systems from Data Streams in Real-Time

P. Angelov, Xiaowei Zhou, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Flexible models with evolving structure

Dimitar Filev, P. Angelov, 2004 .

Evolving Fuzzy Modeling Using Participatory Learning

Plamen Angelov, Nik Kasabov, Dimitar P. Filev, 2010 .

Evolving Single- And Multi-Model Fuzzy Classifiers with FLEXFIS-Class

Plamen P. Angelov, Edwin Lughofer, Xiaowei Zhou, 2007, 2007 IEEE International Fuzzy Systems Conference.

EXPLAINABLE-BY-DESIGN APPROACH FOR COVID-19 CLASSIFICATION VIA CT-SCAN

P. Angelov, E. Soares, 2020, medRxiv.

Evolving rule-based models: A tool for intelligent adaptation

P. Angelov, R. Buswell, Plamen Angelov, 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

Comparison of approaches for identification of all-data cloud-based evolving systems

Igor Škrjanc, Plamen Angelov, Sašo Blažič, 2015 .

Evolving Clustering of Web Documents

P. Angelov, A. Evans, Xiaowei Zhou Lancaster, 2006 .

ARFA: Automated real-time flight data analysis using evolving clustering, classifiers and recursive density estimation

Plamen P. Angelov, Denis Kolev, Garegin Markarian, 2013, 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Fuzzy optimal control

Dimitar Filev, P. Angelov, 1992 .

Supplementary Crossover Operator for Genetic Algorithms based on the Center-of-Gravity Paradigm

P. Angelov, 2001 .

Co-ordinated Airborne Studies in the Tropics (CAST)

Butler, Hyde, Harris, 2017 .

Institutional Repository Evolving rules-based control

P. Angelov, R. Buswell, J. Wright, 2017 .

Proceedings of the 2013 International Joint Conference on Neural Networks

Plamen Angelov, Peter Erdi, Daniel Levine, 2013 .

Proceedings of the 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems

Nikola Kasabov, Edwin Lughofer, Plamen Angelov, 2013 .

Fuzzy Models of Evolvable Granularity

Dimitar Filev, N. Kasabov, P. Angelov, 2010 .

Empirical Approach—Introduction

P. Angelov, Xiaowei Gu, 2018, Empirical Approach to Machine Learning.

Delve into Neural Activations: Towards Understanding Dying Neurons

P. Angelov, Ziping Jiang, Yunpeng Wang, 2022 .

Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World

Majid Sarrafzadeh, Luca Romeo, Farshad Firouzi, 2021, IEEE Internet of Things Journal.

Automatic Extraction and Labelling of Memorial Objects From 3 D Point Clouds

P. Atkinson, P. Angelov, T. Viney, 2021 .

An Improved Explainable Point Cloud Classifier (XPCC)

Nicholas I. Arnold, P. Atkinson, P. Angelov, 2023, IEEE Transactions on Artificial Intelligence.

GEFS: 2008 3rd international workshop on genetic and evolutionary fuzzy systems

Frank Klawonn, Oscar Cordón, Plamen Angelov, 2008 .

Proceedings of the IEEE Conference on Cybernetics 2013

José del R. Millán, Ajith Abraham, Plamen Angelov, 2013 .

Soft Computing Applied to Swarm Robotics

Oscar Castillo, Nadia Nedjah, Luiza de Macedo Mourelle, 2017 .

Age and Gender Recognition using Convolution Neural Network

P. Angelov, Gowtham S Gowda, Akash, 2020 .

AI-enabled Microscopic Blood Analysis for Microfluidic COVID-19 Hematology

Richard M. Jiang, P. Angelov, P. Chazot, 2020, 2020 5th International Conference on Computational Intelligence and Applications (ICCIA).

Advances in Big Data - Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece

Yannis Manolopoulos, Lazaros S. Iliadis, Plamen Angelov, 2017, INNS Conference on Big Data.

Evolving Rule-based Control

Plamen Angelov, Jonathan A. Wright, Richard A. Buswell, 2001 .

Multiclass Fuzzily Weighted Adaptive-Boosting-Based Self-Organizing Fuzzy Inference Ensemble Systems for Classification

P. Angelov, Xiaowei Gu, 2022, IEEE Transactions on Fuzzy Systems.

Adaptive Resilience for Computer Networks

David Hutchison, Plamen Angelov, Paul Smith, 2012 .

On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork

P. Angelov, J. Ueyama, Amokh Varma, 2022, Autonomous Agents and Multi-Agent Systems.

An Interpretable Deep Semantic Segmentation Method for Earth Observation

P. Angelov, P. Mathieu, E. Soares, 2022, 2022 IEEE 11th International Conference on Intelligent Systems (IS).

Graph-context Attention Networks for Size-varied Deep Graph Matching

P. Angelov, Hossein Rahmani, Zheheng Jiang, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Self-Evolving Data Cloud-Based PID-Like Controller for Nonlinear Uncertain Systems

Plamen Angelov, Hang Wang, Hai-Jun Rong, 2021, IEEE Transactions on Industrial Electronics.

Intelligent adaptive systems

Plamen Angelov, Mincho Hadjiski, P. Angelov, 2002 .

Evolving computational intelligence systems

Nikola Kasabov, Plamen Angelov, N. Kasabov, 2005 .

Classification of carcinoma kidney tissue status based on the data of protein expression using LS- SVM

P. Angelov, R. Guthke, F. Eggeling, 2003 .

Brief Introduction to Computational Intelligence

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

PANFIS: A Novel Incremental Learning Machine

Plamen P. Angelov, Mahardhika Pratama, Sreenatha G. Anavatti, 2014, IEEE Transactions on Neural Networks and Learning Systems.

A distance-type-insensitive clustering approach

Xiaowei Gu, Plamen Angelov, Zhijin Zhao, 2019, Appl. Soft Comput..

A method for autonomous data partitioning

Plamen P. Angelov, Xiaowei Gu, José C. Prı́ncipe, 2018, Inf. Sci..

A real-time approach for autonomous detection and tracking of moving objects from UAV

Pouria Sadeghi-Tehran, Plamen Angelov, Christopher Clarke, 2014, 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).

Fully online clustering of evolving data streams into arbitrarily shaped clusters

Plamen Angelov, Richard Hyde, Angus Robert MacKenzie, 2017, Inf. Sci..

Interpretable policies for reinforcement learning by empirical fuzzy sets

Plamen P. Angelov, Chengliang Yin, Jianfeng Huang, 2020, Eng. Appl. Artif. Intell..

Evolving Systems: Review

Plamen Angelov, Jose A. Iglesias, P. Angelov, 2017 .

IRootLab: a free and open-source MATLAB toolbox for vibrational biospectroscopy data analysis

Plamen P. Angelov, Paul L. Carmichael, Francis L. Martin, 2013, Bioinform..

Evolving Takagi‐Sugeno Fuzzy Systems from Streaming Data (eTS+)

Plamen Angelov, P. Angelov, 2010 .

Advances in Computational Intelligence Systems - Contributions Presented at the 18th UK Workshop on Computational Intelligence, September 5-7, 2018, Nottingham, UK

Plamen Angelov, Alexander Gegov, Chrisina Jayne, 2016, UKCI.

A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

Plamen Angelov, Zulfiqar Habib, Allah Bux Sargano, 2017 .

Human Action Recognition from Multiple Views Based on View-Invariant Feature Descriptor Using Support Vector Machines

Plamen Angelov, Zulfiqar Habib, Allah Bux Sargano, 2016 .

Evolving Fuzzy-Rule-Based Classifiers From Data Streams

Plamen P. Angelov, Xiaowei Zhou, P. Angelov, 2008, IEEE Transactions on Fuzzy Systems.

An Approach to Autonomous Self-localization of a Mobile Robot in Completely Unknown Environment using Evolving Fuzzy Rule-based Classifier

Plamen Angelov, Xiaowei Zhou, P. Angelov, 2007 .

An approach to online identification of Takagi-Sugeno fuzzy models

D.P. Filev, P.P. Angelov, Dimitar Filev, 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

SARS-CoV-2 CT-scan dataset:A large dataset of real patients CT scans for SARS-CoV-2 identification

Plamen Angelov, Eduardo Soares, Sarah Biaso, 2020 .

An Approach to Real-time Color-based Object Tracking

P. Angelov, H. Ahmed, M.M. Asif, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

DEC: Dynamically Evolving Clustering and Its Application to Structure Identification of Evolving Fuzzy Models

Plamen P. Angelov, Rashmi Dutta Baruah, P. Angelov, 2014, IEEE Transactions on Cybernetics.

Online learning and prediction of data streams using dynamically evolving fuzzy approach

Plamen P. Angelov, Rashmi Dutta Baruah, P. Angelov, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Design and tuning of fuzzy systems

Plamen Angelov, Jose Antonio Iglesias, P. Angelov, 2012 .

Advances in classification of EEG signals via evolving fuzzy classifiers and dependant multiple HMMs

Plamen P. Angelov, Costas S. Xydeas, Shih-Yang Chiao, 2006, Comput. Biol. Medicine.

Automatic scene recognition for low-resource devices using evolving classifiers

Plamen P. Angelov, Javier Andreu, Rashmi Dutta Baruah, 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

A Predictive Controller for Object Tracking of a Mobile Robot

Plamen Angelov, Chengwei Wang, Xiaowei Zhou, 2008 .

ATDT: Autonomous Template-Based Detection and Tracking of Objects from Airborne Camera

Plamen P. Angelov, Pouria Sadeghi-Tehran, P. Angelov, 2014, IEEE Conf. on Intelligent Systems.

Autonomous learning for fuzzy systems: a review

J. Han, P. Angelov, Q. Shen, 2022, Artificial Intelligence Review.

Data density based clustering

Plamen Angelov, Richard Hyde, P. Angelov, 2014, 2014 14th UK Workshop on Computational Intelligence (UKCI).

Evolving human activity classifier from sensor streams

Plamen P. Angelov, Araceli Sanchis, Agapito Ledezma, 2011, 2011 IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS).

Human Activity Recognition Based on Evolving Fuzzy Systems

Plamen P. Angelov, Araceli Sanchis, Agapito Ledezma, 2010, Int. J. Neural Syst..

Evolving classification of agents’ behaviors: a general approach

Plamen P. Angelov, Araceli Sanchis, Agapito Ledezma, 2010, Evol. Syst..

Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier

Plamen P. Angelov, Luiz Affonso Guedes, Bruno Sielly Jales Costa, 2015, Neurocomputing.

Dynamically evolving clustering for data streams

Plamen P. Angelov, Rashmi Dutta Baruah, Diganta Baruah, 2014, 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Autonomous Learning Systems: From Data Streams to Knowledge in Real-time

Plamen Angelov, P. Angelov, 2013 .

Evolving local means method for clustering of streaming data

Plamen P. Angelov, Rashmi Dutta Baruah, P. Angelov, 2012, 2012 IEEE International Conference on Fuzzy Systems.

Evolving Intelligent Systems: Methodology and Applications

Plamen Angelov, Dimitar Petrov Filev, Nik Kasabov, 2010 .

Look‐a‐Like: A Fast Content‐Based Image Retrieval Approach Using a Hierarchically Nested Dynamically Evolving Image Clouds and Recursive Local Data Density

Pouria Sadeghi-Tehran, Plamen Angelov, P. Angelov, 2017, Int. J. Intell. Syst..

An analytical method for solving a type of fuzzy optimization problems, control and cybernetics.

Plamen Angelov, P. Angelov, 1995 .

Towards Explainable Deep Neural Networks (xDNN)

Plamen Angelov, Eduardo Soares, P. Angelov, 2019, Neural Networks.

Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference: Proceedings of the EANN 2020

Robert Kozma, Chrisina Jayne, Elias Pimenidis, 2020, EANN.

Deep Learning-Based Automated Forest Health Diagnosis From Aerial Images

Plamen Angelov, Richard Jiang, Chloe Barnes, 2020, IEEE Access.

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Radu-Emil Precup, Plamen Angelov, Moamar Sayed Mouchaweh, 2015, Comput. Ind..

An approach to model-based fault detection in industrial measurement systems with application to engine test benches

Edwin Lughofer, Plamen Angelov, Carlos Guardiola, 2006 .

Building Interpretable Systems in Real Time

Plamen Angelov, Dimitar P. Filev, Nik Kasabov, 2010 .

Autonomous Learning Systems in Mobile Robotics

Plamen Angelov, P. Angelov, 2012 .

Robust Evolving Cloud-based Controller in normalized data space for heat-exchanger plant

Igor Skrjanc, Plamen P. Angelov, Saso Blazic, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A Robust Evolving Cloud-Based Controller

Igor Skrjanc, Plamen P. Angelov, Saso Blazic, 2015, Handbook of Computational Intelligence.

Robust evolving cloud-based controller for a hydraulic plant

Igor Skrjanc, Plamen P. Angelov, Saso Blazic, 2013, 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Self-evolving parameter-free Rule-based Controller

Héctor Pomares, Ignacio Rojas, Plamen P. Angelov, 2012, 2012 IEEE International Conference on Fuzzy Systems.

An approach for fuzzy rule-base adaptation using on-line clustering

Plamen P. Angelov, P. Angelov, 2004, Int. J. Approx. Reason..

Flexible models with evolving structure

Plamen Angelov, Dimitar Petrov Filev, Dimitar Filev, 2002, Proceedings First International IEEE Symposium Intelligent Systems.

Analysis of adaptation law of the robust evolving cloud-based controller

Igor Skrjanc, Plamen Angelov, Saso Blazic, 2015, 2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS).

An approach to automatic real‐time novelty detection, object identification, and tracking in video streams based on recursive density estimation and evolving Takagi–Sugeno fuzzy systems

Plamen P. Angelov, Ramin Ramezani, Pouria Sadeghi-Tehran, 2011, Int. J. Intell. Syst..

Optimization in an intuitionistic fuzzy environment

Plamen P. Angelov, P. Angelov, 1997, Fuzzy Sets Syst..

Stability of Evolving Fuzzy Systems Based on Data Clouds

Plamen P. Angelov, Xiaowei Gu, Hai-Jun Rong, 2018, IEEE Transactions on Fuzzy Systems.

Multi-objective optimisation in air-conditioning systems : comfort/discomfort definition by IF sets.

Plamen Angelov, P. Angelov, 2001 .

Crispification : defuzzification over intuitionistic fuzzy sets.

Plamen Angelov, P. Angelov, 1995 .

Brief Introduction to Statistical Machine Learning

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

Recursive SVM Based on TEDA

Plamen P. Angelov, Dmitry Kangin, P. Angelov, 2015, SLDS.

A center-of-gravity-based recombination operator for genetic algorithms

Plamen Angelov, J. A. Wright, P. Angelov, 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

AURORA: autonomous real-time on-board video analytics

Plamen Angelov, Christopher Clarke, Pouria Sadeghi-Tehran, 2017, Neural Computing and Applications.

ARTOD: Autonomous Real Time Objects Detection by a Moving Camera Using Recursive Density Estimation

Plamen Angelov, Pouria Sadeghi-Tehran, P. Angelov, 2016 .

RTSDE: Recursive total-sum-distances-based density estimation approach and its application for autonomous real-time video analytics

Plamen Angelov, Ashley Wilding, P. Angelov, 2014, 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).

Real-time novelty detection in video using background subtraction techniques: State of the art a practical review

Plamen Angelov, Gruffydd Morris, P. Angelov, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Forecasting time-series for NN GC1 using Evolving Takagi-Sugeno (eTS) Fuzzy Systems with on-line inputs selection

Plamen P. Angelov, Javier Andreu, P. Angelov, 2010, International Conference on Fuzzy Systems.

A Fast Recursive Approach to Autonomous Detection, Identification and Tracking of Multiple Objects in Video Streams under Uncertainties

Plamen P. Angelov, Ramin Ramezani, Pouria Sadeghi-Tehran, 2010, IPMU.

A fast approach to novelty detection in video streams using recursive density estimation

P. Angelov, Xiaowei Zhou, R. Ramezani, 2008, 2008 4th International IEEE Conference Intelligent Systems.

Autonomous novelty detection and object tracking in video streams using evolving clustering and Takagi-Sugeno type neuro-fuzzy system

Plamen P. Angelov, Ramin Ramezani, Xiaowei Zhou, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Self-Training Hierarchical Prototype-based Ensemble Framework for Remote Sensing Scene Classification

Plamen P. Angelov, Peter M. Atkinson, Xiaowei Gu, 2021, Inf. Fusion.

A Semi-Supervised Deep Rule-Based Approach for Complex Satellite Sensor Image Analysis

Xiaowei Gu, Peter M. Atkinson, Ce Zhang, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Explainable artificial intelligence: an analytical review

Plamen P. Angelov, Eduardo A. Soares, Richard M. Jiang, 2021, WIREs Data Mining Knowl. Discov..

Self-Organised direction aware data partitioning algorithm

Xiaowei Gu, Plamen Angelov, José Carlos Príncipe, 2018, Inf. Sci..

A new type of distance metric and its use for clustering

J. Príncipe, P. Angelov, D. Kangin, 2017, Evolving Systems.

A new type of distance metric and its use for clustering

Plamen P. Angelov, Xiaowei Gu, José Carlos Príncipe, 2017, Evol. Syst..

Robust classification of low-grade cervical cytology following analysis with ATR-FTIR spectroscopy and subsequent application of self-learning classifier eClass

Plamen P. Angelov, Jemma G. Kelly, Pierre L. Martin-Hirsch, 2010, Analytical and bioanalytical chemistry.

Parsimonious random vector functional link network for data streams

Plamen P. Angelov, Mahardhika Pratama, Meng Joo Er, 2017, Inf. Sci..

Extracting biological information with computational analysis of Fourier-transform infrared (FTIR) biospectroscopy datasets: current practices to future perspectives.

Francis L Martin, Plamen P Angelov, Paul L Carmichael, 2012, The Analyst.

Fuzzily Connected Multimodel Systems Evolving Autonomously From Data Streams

Plamen P. Angelov, P. Angelov, 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Architectures for evolving fuzzy rule-based classifiers

Plamen P. Angelov, Edwin Lughofer, Dimitar Filev, 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

Evolving Fuzzy Rule-based Classifiers

F. Klawonn, Xiaowei Zhou, P. Angelov, 2007, 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing.

On-line Evolving Clustering of Web Documents

Plamen Angelov, A Evans, Xiaowei Zhou, 2006 .

Evolving Intelligent Systems, eIS

Plamen Angelov, Nik Kasabov, N. Kasabov, 2006 .

Nature-Inspired Methods for Knowledge Generation from Data in Real-Time

Plamen Angelov, P. Angelov, 2006 .

PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework

P. Angelov, N. Suri, Zhengxin Yu, 2022, 2022 18th International Conference on Mobility, Sensing and Networking (MSN).

Evolving fuzzy classifiers using different model architectures

E. Lughofer, P. Angelov, X. Zhou, 2008, Fuzzy Sets Syst..

Vision Based Human Activity Recognition: A Review

Plamen Angelov, Zulfiqar Habib, Allah Bux Sargano, 2016, UKCI.

A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion

Xiaowei Gu, Zhao-Xu Yang, Muhammad Aurangzeb Khan, 2019, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Data Partitioning—Empirical Approach

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

Empirical Fuzzy Sets and Systems

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

How Best to Design Fuzzy Sets and Systems - In Memory of Prof. Lotfi A. Zadeh

Plamen Angelov, P. Angelov, 2018, WILF.

Autonomous Learning Multimodel Systems From Data Streams

Plamen P. Angelov, Xiaowei Gu, José C. Príncipe, 2018, IEEE Transactions on Fuzzy Systems.

Self-organising fuzzy logic classifier

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2018, Inf. Sci..

Empirical Fuzzy Sets

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2018, Int. J. Intell. Syst..

Autonomous learning multi-model classifier of 0-Order (ALMMo-0)

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2017, 2017 Evolving and Adaptive Intelligent Systems (EAIS).

Autonomously evolving classifier TEDAClass

Plamen Angelov, Dmitry Kangin, José Antonio Iglesias, 2016, Inf. Sci..

Evolving clustering, classification and regression with TEDA

Plamen Angelov, Dmitry Kangin, P. Angelov, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A practical implementation of self-evolving cloud-based control of a pilot plant

Igor Skrjanc, Plamen Angelov, Saso Blazic, 2013, 2013 IEEE International Conference on Cybernetics (CYBCO).

A new type of simplified fuzzy rule-based system

Plamen P. Angelov, Ronald R. Yager, R. Yager, 2012, Int. J. Gen. Syst..

Simplified fuzzy rule-based systems using non-parametric antecedents and relative data density

Plamen P. Angelov, Ronald R. Yager, R. Yager, 2011, 2011 IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS).

A simple fuzzy rule-based system through vector membership and kernel-based granulation

Plamen P. Angelov, Ronald R. Yager, R. Yager, 2010, 2010 5th IEEE International Conference Intelligent Systems.

Guest Editorial Evolving Fuzzy Systems–-Preface to the Special Section

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2008, IEEE Transactions on Fuzzy Systems.

Evolving fuzzy systems

Plamen P. Angelov, P. Angelov, 2008, Scholarpedia.

Explaining Deep Learning Models Through Rule-Based Approximation and Visualization

Dimitar Filev, Plamen Angelov, Eduardo Soares, 2020, IEEE Transactions on Fuzzy Systems.

Uniformly Stable Backpropagation Algorithm to Train a Feedforward Neural Network

Plamen P. Angelov, José de Jesús Rubio, Jaime Pacheco, 2011, IEEE Transactions on Neural Networks.

A Massively Parallel Deep Rule-Based Ensemble Classifier for Remote Sensing Scenes

Plamen P. Angelov, Xiaowei Gu, Peter M. Atkinson, 2018, IEEE Geoscience and Remote Sensing Letters.

Autonomous visual self-localization in completely unknown environment

Plamen P. Angelov, Xiaowei Zhou, P. Angelov, 2007, 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems.

A randomized neural network for data streams

Chee Peng Lim, Plamen P. Angelov, Mahardhika Pratama, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Automatic Extraction and Labelling of Memorial Objects From 3D Point Clouds

Plamen Angelov, Peter Atkinson, Nicholas Arnold, 2021 .

Fuzzy systems design: direct and indirect approaches

Plamen P. Angelov, Costas S. Xydeas, P. Angelov, 2006, Soft Comput..

Statistically Evolving Fuzzy Inference System for Non-Gaussian Noises

Plamen Angelov, Hai-Jun Rong, Zhao-Xu Yang, 2022, IEEE Transactions on Fuzzy Systems.

Particle Swarm Optimized Autonomous Learning Fuzzy System

Xiaowei Gu, Qiang Shen, Plamen P Angelov, 2020, IEEE Transactions on Cybernetics.

An evolving approach to data streams clustering based on typicality and eccentricity data analytics

Plamen P. Angelov, Luiz Affonso Guedes, Clauber Gomes Bezerra, 2020, Inf. Sci..

A new online clustering approach for data in arbitrary shaped clusters

Plamen Angelov, Richard Hyde, P. Angelov, 2015, 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF).

Real-Time Fault Detection Using Recursive Density Estimation

Plamen Angelov, Luiz Affonso Guedes, Bruno Sielly Jales Costa, 2014, Journal of Control, Automation and Electrical Systems.

Real-Time Fault Detection Using Recursive Density Estimation

L. A. Guedes, P. Angelov, B. Costa, 2014, Journal of Control, Automation and Electrical Systems.

Robust evolving cloud-based PID control adjusted by gradient learning method

Igor Skrjanc, Plamen P. Angelov, Saso Blazic, 2014, 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

On-line identification of MIMO evolving Takagi- Sugeno fuzzy models

Plamen P. Angelov, Dimitar Filev, Costas S. Xydeas, 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

Identification of evolving fuzzy rule-based models

Plamen P. Angelov, Richard A. Buswell, P. Angelov, 2002, IEEE Trans. Fuzzy Syst..

Evolving Fuzzy Rule-Based Models

Plamen Angelov, P. Angelov, 2000 .

HVAC SYSTEMS SIMULATION: A SELF-STRUCTURING FUZZY RULE- BASED APPROACH

Plamen Angelov, Jonathan A. Wright, V. I. Hanby, 2000 .

Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning

Nathanael L. Baisa, P. Angelov, Hossein Rahmani, 2021, International Conference on Image Processing Theory Tools and Applications.

Handling drifts and shifts in on-line data streams with evolving fuzzy systems

Plamen P. Angelov, Edwin Lughofer, P. Angelov, 2011, Appl. Soft Comput..

Editorial

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2010, Evolutionary Systematics.

Self-organizing fuzzy inference ensemble system for big streaming data classification

Plamen P. Angelov, Xiaowei Gu, Zhijin Zhao, 2021, Knowl. Based Syst..

About analytical solving fuzzy mathematical programming problem.

Plamen Angelov, P. Angelov, 1993 .

Data-driven evolving fuzzy systems using eTS and FLEXFIS: comparative analysis

Plamen P. Angelov, Edwin Lughofer, P. Angelov, 2008, Int. J. Gen. Syst..

Evolving fuzzy systems for data streams: a survey

Plamen P. Angelov, Rashmi Dutta Baruah, P. Angelov, 2011, WIREs Data Mining Knowl. Discov..

Fair-by-design explainable models for prediction of recidivism pdf

Plamen Angelov, Eduardo Soares, P. Angelov, 2019, ArXiv.

Semantic categorization of web-based documents

P. Angelov, T. Evans, 2004 .

Human action recognition using deep rule-based classifier

Xiaowei Gu, Plamen Angelov, Allah Bux Sargano, 2020, Multimedia Tools and Applications.

Semi-supervised deep rule-based approach for image classification

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2018, Appl. Soft Comput..

Evolving Rule-Based Models: A Tool For Design Of Flexible Adaptive Systems

Plamen Angelov, P. Angelov, 2002 .

Stability Analysis for an Online Evolving NeuroFuzzy Recurrent Network

Plamen Angelov, Nik Kasabov, Dimitar P. Filev, 2010 .

Evolving Takagi-Sugeno fuzzy systems from data streams (eTS+).

Plamen Angelov, P. Angelov, 2010 .

Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models

Plamen P. Angelov, Dimitar Filev, Dimitar Filev, 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

A Generalized Methodology for Data Analysis

Plamen P. Angelov, Xiaowei Gu, José Carlos Príncipe, 2018, IEEE Transactions on Cybernetics.

Empirical Data Analytics

Xiaowei Gu, Plamen Angelov, Dmitry Kangin, 2017, Int. J. Intell. Syst..

Clustering as a tool for self-generation of intelligent systems : a survey.

Plamen Angelov, Rashmi Dutta Baruah, P. Angelov, 2010 .

Gender and Age Classification of Human Faces for Automatic Detection of Anomalous Human Behaviour

Xiaofeng Wang, Plamen P. Angelov, Azliza Mohd Ali, 2017, 2017 3rd IEEE International Conference on Cybernetics (CYBCON).

Empirical Approach to Learning from Data (Streams)

Plamen Angelov, P. Angelov, 2018, International Conference on Enterprise Information Systems.

Challenges in Deep Learning

Alessandro Sperduti, Plamen Angelov, A. Sperduti, 2016, ESANN.

Editorial: Special issue on recent progress in autonomous machine learning

P. Angelov, E. Lughofer, Mahardhika Pratama, 2022, Inf. Sci..

Anomaly detection based on eccentricity analysis

Plamen Angelov, P. Angelov, 2014, 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).

Dynamically evolving fuzzy classifier for real-time classification of data streams

Plamen P. Angelov, Rashmi Dutta Baruah, Diganta Baruah, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Analysis of evolving social network: methods and results from cell phone dataset case study

Plamen P. Angelov, Rashmi Dutta Baruah, P. Angelov, 2013, Int. J. Soc. Netw. Min..

Self-Organising and Self-Learning Model for Soybean Yield Prediction

Plamen P. Angelov, Mona Alghamdi, Raul Gimenez, 2019, 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS).

A fuzzy controller with evolving structure

Plamen P. Angelov, P. Angelov, 2004, Inf. Sci..

Outside the box: an alternative data analytics framework

Plamen Angelov, P. Angelov, 2014, J. Autom. Mob. Robotics Intell. Syst..

Toward Anthropomorphic Machine Learning

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2018, Computer.

Vehicle Plate Recognition Using Improved Neocognitron Neural Network

Plamen P. Angelov, Dmitry Kangin, George Kolev, 2013, ICANN.

Explainable Density-Based Approach for Self-Driving Actions Classification

Dimitar Filev, Plamen Angelov, Subramanya Nageshrao, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Human action recognition using transfer learning with deep representations

Xiaofeng Wang, Plamen Angelov, Zulfiqar Habib, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A methodology for modeling HVAC components using evolving fuzzy rules

Jonathan A. Wright, V. I. Hanby, Richard A. Buswell, 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

A self‐adaptive synthetic over‐sampling technique for imbalanced classification

P. Angelov, E. Soares, Xiaowei Gu, 2019, Int. J. Intell. Syst..

Self-Organizing Fuzzy Belief Inference System for Classification

P. Angelov, Q. Shen, Xiaowei Gu, 2022, IEEE Transactions on Fuzzy Systems.

Foreign currency exchange rate prediction using neuro-fuzzy systems

Plamen P. Angelov, Xiaowei Gu, David Chek Ling Ngo, 2018, INNS Conference on Big Data.

Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology

Plamen Angelov, Pouria Sadeghi-Tehran, Nicolas Virlet, 2019, J. Imaging.

Multilayer Evolving Fuzzy Neural Networks

J. Han, P. Angelov, Q. Shen, 2023, IEEE Transactions on Fuzzy Systems.

Local optimality of self-organising neuro-fuzzy inference systems

Xiaowei Gu, Hai-Jun Rong, Plamen Angelov, 2019, Inf. Sci..

Correntropy-Based Evolving Fuzzy Neural System

Plamen P. Angelov, Badong Chen, Hai-Jun Rong, 2018, IEEE Transactions on Fuzzy Systems.

Online evolving fuzzy rule-based prediction model for high frequency trading financial data stream

Plamen P. Angelov, Xiaowei Gu, Georgi Gaydadjiev, 2016, 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Empirical Approach to Machine Learning

P. Angelov, Xiaowei Gu, 2018, Studies in Computational Intelligence.

Evolutionary Synthesis of HVAC System Configurations: Algorithm Development (RP-1049)

Plamen Angelov, Yi Zhang, Jonathan A. Wright, 2008 .

Actively Semi-Supervised Deep Rule-based Classifier Applied to Adverse Driving Scenarios

Plamen Angelov, Bruno Costa, Eduardo Soares, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Towards Large Scale Ad-hoc Teamwork

Leandro Soriano Marcolino, Plamen Angelov, Thomas Pinder, 2018, 2018 IEEE International Conference on Agents (ICA).

Autonomous Learning Multiple-Model zero-order classifier for heart sound classification

Xiaowei Gu, Plamen Angelov, Eduardo Soares, 2020, Appl. Soft Comput..

A new evolving clustering algorithm for online data streams

Plamen P. Angelov, Luiz Affonso Guedes, Clauber Gomes Bezerra, 2016, 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Creating Evolving User Behavior Profiles Automatically

Plamen P. Angelov, Araceli Sanchis, Agapito Ledezma, 2012, IEEE Transactions on Knowledge and Data Engineering.

Self-boosting first-order autonomous learning neuro-fuzzy systems

Xiaowei Gu, Plamen Angelov, P. Angelov, 2019, Appl. Soft Comput..

Automated Person Identification Framework Based on Fingernails and Dorsal Knuckle Patterns

P. Angelov, Bryan M. Williams, M. Alghamdi, 2021, 2021 IEEE Symposium Series on Computational Intelligence (SSCI).

Empirical data analysis: A new tool for data analytics

Plamen P. Angelov, Xiaowei Gu, José Carlos Príncipe, 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Anomaly Detection—Empirical Approach

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

Autonomous anomaly detection

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2017, 2017 Evolving and Adaptive Intelligent Systems (EAIS).

Detecting Anomalous Behaviour Using Heterogeneous Data

Xiaowei Gu, Plamen Angelov, Azliza Mohd Ali, 2016, UKCI.

A Method for Predicting Quality of the Crude Oil Distillation

P. Angelov, Xiaowei Zhou, J.J. Macias, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Deep rule-based classifier with human-level performance and characteristics

Plamen P. Angelov, Xiaowei Gu, P. Angelov, 2018, Inf. Sci..

Syrian hamster embryo (SHE) assay (pH 6.7) coupled with infrared spectroscopy and chemometrics towards toxicological assessment.

Francis L Martin, Plamen P Angelov, Paul L Carmichael, 2010, The Analyst.

Automatic Design Synthesis and Optimization of Component-Based Systems by Evolutionary Algorithms

Plamen P. Angelov, Y. Zhang, Jonathan A. Wright, 2003, GECCO.

An evolving machine learning method for human activity recognition systems

Plamen P. Angelov, Javier Andreu, P. Angelov, 2013, J. Ambient Intell. Humaniz. Comput..

Detecting and Reacting on Drifts and Shifts in On-Line Data Streams with Evolving Fuzzy Systems

Plamen P. Angelov, Edwin Lughofer, P. Angelov, 2009, IFSA/EUSFLAT Conf..

Evolving fuzzy inferential sensors for process industry

Plamen P. Angelov, Xiaowei Zhou, Arthur K. Kordon, 2008, 2008 3rd International Workshop on Genetic and Evolving Systems.

Delve Into Neural Activations: Toward Understanding Dying Neurons

P. Angelov, Ziping Jiang, Yunpeng Wang, 2023, IEEE Transactions on Artificial Intelligence.

Interpretable-through-prototypes deepfake detection for diffusion models

P. Angelov, D. Kangin, Agil Aghasanli, 2023, 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

Evolving Intelligent Systems

Plamen Angelov, Rashmi Dutta Baruah, Diganta Baruah, 2020 .

Transparent Deep Rule-Based Classifiers

Xiaowei Gu, Plamen Angelov, P. Angelov, 2018, Empirical Approach to Machine Learning.

Intuitionistic fuzzy optimisation.

Plamen Angelov, P. Angelov, 1995 .

Evolving Rule-Based Models: A Tool For Design Of Flexible Adaptive Systems

Plamen Angelov, P. Angelov, Plamen Angelov, 2002 .

Evolving Inferential Sensors in the Chemical Process Industry

Plamen Angelov, Arthur K. Kordon, P. Angelov, 2010 .

Real-Time Recognition of Calling Pattern and Behaviour of Mobile Phone Users through Anomaly Detection and Dynamically-Evolving Clustering

Araceli Sanchis, Plamen Angelov, Agapito Ledezma, 2017 .

An evolving approach to unsupervised and Real-Time fault detection in industrial processes

Plamen P. Angelov, Luiz Affonso Guedes, Clauber Gomes Bezerra, 2016, Expert Syst. Appl..

Toward Anthropomorphic Machine Learning

P. Angelov, Xiaowei Gu, 2018, Computer.

A self‐adaptive synthetic over‐sampling technique for imbalanced classification

Xiaowei Gu, Plamen P Angelov, Eduardo Almeida Soares, 2019, Int. J. Intell. Syst..

Appendix A: Mathematical Foundations

Plamen Angelov, P. Angelov, 2012 .

Adaptive Inferential Sensors Based on Evolving Fuzzy Models

P. Angelov, A. Kordon, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

P. Angelov, E. Soares, N. Suri, 2022, 2022 IEEE Symposium Series on Computational Intelligence (SSCI).

A generalized approach to fuzzy optimization

Plamen Angelov, P. Angelov, 1994, Int. J. Intell. Syst..

Detecting and learning from unknown by extremely weak supervision: exploratory classifier (xClass)

Plamen Angelov, Eduardo Soares, P. Angelov, 2021, Neural Computing and Applications.

Novelty Detection and Learning from Extremely Weak Supervision pdf

Plamen Angelov, Eduardo Soares, P. Angelov, 2019, ArXiv.

Francis L Martin, Plamen P Angelov, Paul L Carmichael, 2014, Journal of biophotonics.

Towards interpretable-by-design deep learning algorithms

P. Angelov, D. Kangin, Ziyang Zhang, 2023, ArXiv.

Rothamsted Repository Download

P. Angelov, M. Hawkesford, N. Virlet, 2022 .

A large multiclass dataset of CT scans for COVID-19 identification

P. Angelov, E. Soares, M. Cury, 2023, Evol. Syst..

Evolving Fuzzy Classifier for Novelty Detection and Landmark Recognition by Mobile Robots

Plamen P. Angelov, Xiaowei Zhou, P. Angelov, 2007, Mobile Robots.

Coordinated Airborne Studies in the Tropics (CAST)

Butler, Hyde, Harris, 2017, Bulletin of the American Meteorological Society.

Online fault detection based on Typicality and Eccentricity Data Analytics

Plamen P. Angelov, Luiz Affonso Guedes, Clauber Gomes Bezerra, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A new unsupervised approach to fault detection and identification

Plamen P. Angelov, Luiz Affonso Guedes, Bruno Sielly Jales Costa, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Multi-Branch with Attention Network for Hand-Based Person Recognition

P. Angelov, Hossein Rahmani, Sue Black, 2021, 2022 26th International Conference on Pattern Recognition (ICPR).

Symbol recognition with a new autonomously evolving classifier autoclass

Plamen P. Angelov, Xiaowei Zhou, Denis Kolev, 2014, 2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Hybrid modelling of biotechnological processes using neural networks

Plamen Angelov, Georges Bastin, Olivier Bernard, 1999 .