A. Gegov

发表

Decomposition of multivariable systems for distributed fuzzy control

Paul M. Frank, Alexander Gegov, P. Frank, 1995 .

Knowledge-based expert system using a set of rules to assist a tele-operated mobile robot

D. Ndzi, A. Gegov, D. Sanders, 2016 .

A Rule-Based Expert System to Decide on Direction and Speed of a Powered Wheelchair

Malik Haddad, David A. Sanders, Alexander E. Gegov, 2018, IntelliSys.

Web Users and Web Document Classifiers: Emergent Cognitive Phenomena

N. Kushmerick, A. Gegov, M. Dimitrova, 2004 .

Decentralized fuzzy control of multivariable systems by active decomposition of control laws

Paul M. Frank, Alexander Gegov, P. Frank, 1995 .

Multilayer fuzzy control of multivariable processes by direct decomposition

A. Gegov, A. Gegov, A. Nabout, 1995, Proceedings of 1995 American Control Conference - ACC'95.

Intelligent Agent-based Technique For Virtual Machine Resource Allocation For Energy-Efficient Cloud Data Centres

A. Gegov, M. Adda, Ogechukwu Okonor, 2020, WSEAS TRANSACTIONS ON COMMUNICATIONS.

Formal presentation of fuzzy systems with multiple sensor inputs

A. Gegov, Dimitrios Maketas, 2005 .

Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic Review

A. Gegov, Alice Good, A. Hopgood, 2022, SN Computer Science.

Conventional and Structure Based Sentiment Analysis: A Survey

Alexander Gegov, Rinat Khusainov, Omar Ali, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

FN-TOPSIS: Fuzzy Networks for Ranking Traded Equities

Abdul Malek Yaakob, Antoaneta Serguieva, Alexander Gegov, 2017, IEEE Transactions on Fuzzy Systems.

Implementing Adaptive Vectorial Centroid in Bayesian Logistic Regression for Interval Type-2 Fuzzy Sets

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, A. Gegov, 2015, IJCCI.

Bayesian logistic regression using Vectorial Centroid for interval type-2 fuzzy sets

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, A. Gegov, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

Ranking of interval type-2 fuzzy numbers based on centroid point and spread

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, Ahmad Syafadhli Abu Bakar, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

Validation of methods for ranking fuzzy numbers in decision making

Alexander E. Gegov, Ahmad Syafadhli Abu Bakar, A. Gegov, 2015, J. Intell. Fuzzy Syst..

Analysis of systems under probabilistic and fuzzy uncertainty using multi-valued logic

Alexander E. Gegov, Daniela Parashkevova, Krum Ljubenov, 2004, Int. J. Gen. Syst..

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.

Rule Based Systems for Big Data

Han Liu, Mihaela Cocea, Alexander Gegov, 2015 .

Categorization and Construction of Rule Based Systems

Alexander E. Gegov, Han Liu, Frederic T. Stahl, 2014, EANN.

Deep Learning for Pipeline Damage Detection: an Overview of the Concepts and a Survey of the State-of-the-Art

Alexander Gegov, Boriana Vatchova, Sina Razvarz, 2020, 2020 IEEE 10th International Conference on Intelligent Systems (IS).

Complexity Management in Fuzzy Systems - A Rule Base Compression Approach

Alexander E. Gegov, A. Gegov, 2007, Studies in Fuzziness and Soft Computing.

Numerical methods for solving fuzzy equations: A survey

Wen Yu, Alexander Gegov, Sina Razvarz, 2021, Fuzzy Sets Syst..

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

A. Gegov, R. Jafari, Farzad Arabikhan, 2022, Electronics.

Z-Numbers Based TOPSIS Similarity Methodology for Company Performance Assessment in Malaysia

Ku Muhammad Naim Ku Khalif, Alexander Gegov, Ahmad Syafadhli Abu Bakar, 2019, Applying Fuzzy Logic for the Digital Economy and Society.

Z-TOPSIS approach for performance assessment using fuzzy similarity

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, Ahmad Syafadhli Abu Bakar, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Hybrid fuzzy MCDM model for Z-numbers using intuitive vectorial centroid

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, Ahmad Syafadhli Abu Bakar, 2017, J. Intell. Fuzzy Syst..

Confidence levels q‐rung orthopair fuzzy aggregation operators and its applications to MCDM problems

Alexander Gegov, Bhagawati Prasad Joshi, A. Gegov, 2019, Int. J. Intell. Syst..

Rule-based systems: a granular computing perspective

Han Liu, Mihaela Cocea, Alexander Gegov, 2016, Granular Computing.

The Importance of Pipeline Transportation

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2020, Flow Modelling and Control in Pipeline Systems.

Rule based systems and networks: Deterministic and fuzzy approaches

Alexander E. Gegov, Han Liu, Han Liu, 2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS).

Unified framework for construction of rule based classification systems

Han Liu, Frederic Stahl, Frederic T. Stahl, 2015 .

J-measure based hybrid pruning for complexity reduction in classification rules

Han Liu, Frederic Stahl, Frederic T. Stahl, 2013 .

Hybrid ensemble learning approach for generation of classification rules

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2015, 2015 International Conference on Machine Learning and Cybernetics (ICMLC).

Z-Hesitant Fuzzy Network Model with Reliability and Transparency of Information for Decision Systems

Alexander E. Gegov, Siti Fatimah Abdul Rahman, Abdul Malek Yaakob, 2021, International Journal of Computational Intelligence Systems.

Neural Network Approach to Solving Fuzzy Nonlinear Equations Using Z-Numbers

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2020, IEEE Transactions on Fuzzy Systems.

Modeling of Uncertain Nonlinear System With Z-Numbers

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2020 .

A Novel Technique for Solving Fully Fuzzy Nonlinear Systems Based on Neural Networks

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2020, Vietnam. J. Comput. Sci..

Fuzzy Sumudu Transform Approach to Solving Fuzzy Differential Equations With Z-Numbers

Sina Razvarz, Raheleh Jafari, Sajjad Keshtkar, 2018, Advanced Fuzzy Logic Approaches in Engineering Science.

Solving Differential Equations with Z-Numbers by Utilizing Fuzzy Sumudu Transform

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2018, IntelliSys.

A New Computational Method for Solving Fully Fuzzy Nonlinear Systems

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2018, ICCCI.

Fuzzy Modeling for Uncertain Nonlinear Systems Using Fuzzy Equations and Z-Numbers

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2018, UKCI.

Gender-Based Analysis of Zones of Tolerance for Transit Service Quality Considering Intelligent Transportation Systems

Maria Nadia Postorino, Farzad Arabikhan, Alexander Gegov, 2016 .

Control of Flow Rate in Heavy-Oil Pipelines Using PD and PID Controller

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2020 .

Flow Control of Fluid in Pipelines Using PID Controller

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2019, IEEE Access.

Interactive TOPSIS Based Group Decision Making Methodology Using Z-Numbers

Alexander Gegov, Abdul Malek Yaakob, A. Gegov, 2016, Int. J. Comput. Intell. Syst..

Space-Independent Community Detection in Airport Networks

Maria Nadia Postorino, Boriana Vatchova, Emil Gegov, 2016 .

Evolution-based modelling of complex airport networks

Alexander Gegov, Mark Atherton, Emil Gegov, 2011 .

Deriving margins in prostate cancer radiotherapy treatment: comparison of neural network and fuzzy logic models

Nedyalko Petrov, Alexander Gegov, Bongile Mzenda, 2012, Int. J. Bioinform. Res. Appl..

Improving the transparency in fuzzy modelling of radiotherapy margins in cancer treatment

Alexander E. Gegov, David J. Brown, Bongile Mzenda, 2011, 2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

Implementation of a fuzzy model for computation of margins in cancer treatment

Alexander E. Gegov, David J. Brown, Bongile Mzenda, 2010, International Conference on Fuzzy Systems.

A fuzzy convolution model for radiobiologically optimized radiotherapy margins

Bongile Mzenda, Alex Gegov, A. Gegov, 2010, Physics in medicine and biology.

Creation of a NFC Reading System for University Attendance Monitoring with Accessibility Considerations for Powered Wheelchair Users

Malik Haddad, Alexander Gegov, David Sanders, 2020, 2020 IEEE 10th International Conference on Intelligent Systems (IS).

Generalised Fuzzy Bayesian Network with Adaptive Vectorial Centroid

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, A. Gegov, 2015, IFSA-EUSFLAT.

Collaborative rule generation: An ensemble learning approach

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2016, J. Intell. Fuzzy Syst..

Nature and biology inspired approach of classification towards reduction of bias in machine learning

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2016, 2016 International Conference on Machine Learning and Cybernetics (ICMLC).

Application of Deep Learning for the Diagnosis of Cardiovascular Diseases

Alexander E. Gegov, Giovanah Gogi, A. Gegov, 2019, IntelliSys.

Selection of alternatives using fuzzy networks with rule base aggregation

Alexander E. Gegov, Siti Fatimah Abdul Rahman, Abdul Malek Yaakob, 2017, Fuzzy Sets Syst..

Fuzzy Control of Uncertain Nonlinear Systems with Numerical Techniques: A Survey

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2019, UKCI.

Modeling and Control of Uncertain Nonlinear Systems

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2018, 2018 International Conference on Intelligent Systems (IS).

Solution of Dual Fuzzy Equations Using a New Iterative Method

Alexander E. Gegov, Ole-Christoffer Granmo, Sina Razvarz, 2018, ACIIDS.

Aggregation of inconsistent rules for fuzzy rule base simplification

David A. Sanders, Alexander E. Gegov, Boriana Vatchova, 2017, Int. J. Knowl. Based Intell. Eng. Syst..

Multilevel intelligent fuzzy control of oversaturated urban traffic networks

Alexander Gegov, A. Gegov, 1994 .

Interval Type-2 Fuzzy Multi Criteria Decision Making Based on Intuitive Multiple Centroid

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, Noor Zuraidin Mohd Safar, 2020, SCDM.

Cognitive modelling of language acquisition with complex networks

Fernand Gobet, Julian M. Pine, Mark Atherton, 2012 .

Fuzzy risk analysis under influence of non-homogeneous preferences elicitation in fiber industry

Ku Muhammad Naim Ku Khalif, Asma Ahmad Shariff, Alexander Gegov, 2019, Applied Intelligence.

Fuzzy risk analysis under influence of non-homogeneous preferences elicitation in fiber industry

Ahmad Syafadhli Abu Bakar, A. Gegov, A. A. Shariff, 2019, Applied Intelligence.

Ranking of fuzzy numbers based on centroid point and spread

Alexander E. Gegov, Ahmad Syafadhli Abu Bakar, A. Gegov, 2014, J. Intell. Fuzzy Syst..

Rule Based Networks: An Efficient and Interpretable Representation of Computational Models

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2017, J. Artif. Intell. Soft Comput. Res..

Interpretability of Computational Models for Sentiment Analysis

Han Liu, Alexander Gegov, Mihaela Cocea, 2016, Sentiment Analysis and Ontology Engineering.

Network based rule representation for knowledge discovery and predictive modelling

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

The Effect of Baffles on Heat Transfer

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2019, ICINCO.

Rule base simplification in fuzzy systems by aggregation of inconsistent rules

David A. Sanders, Alexander E. Gegov, Farzad Arabikhan, 2015, J. Intell. Fuzzy Syst..

Rule base compression in fuzzy systems by filtration of non-monotonic rules

David A. Sanders, Alexander E. Gegov, Neelamugilan Gobalakrishnan, 2014, J. Intell. Fuzzy Syst..

Advances in fuzzy systems and networks

Alexander E. Gegov, A. Gegov, 2012, 2012 6th IEEE International Conference Intelligent Systems.

Complexity management methodology for fuzzy systems with feedback rule bases

David A. Sanders, Alexander E. Gegov, Boriana Vatchova, 2014, J. Intell. Fuzzy Syst..

A Review on Different Pipeline Defect Detection Techniques

Alexander Gegov, Sina Razvarz, Raheleh Jafari, 2020 .

Non-Iterative Adaptive Control in Multilevel Systems

Todor Stoilov, Alexander Gegov, T. Stoilov, 1989 .

Conceptual Artificial Intelligence framework to Improving English as Second Language

Alexander Gegov, Farzad Arabikhan, Mo Adda, 2020, WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION.

Heuristic Fuzzy Control of Traffic Junctions in Urban Areas

A. Gegov, B. Vatchova, Yordanka Boneva, 2021, 2021 Big Data, Knowledge and Control Systems Engineering (BdKCSE).

Unified Framework for Control of Machine Learning Tasks Towards Effective and Efficient Processing of Big Data

Han Liu, Mihaela Cocea, Alexander Gegov, 2017 .

Ensemble Learning Approaches

Han Liu, Mihaela Cocea, Alexander Gegov, 2016 .

Collaborative decision making by ensemble rule based classification systems

Han Liu, Alexander Gegov, Han Liu, 2015 .

Artificial Intelligence for Medical Image Interpretation Using Expert Knowledge and Machine Learning

A. Gegov, M. Bader-El-Den, A. Hopgood, 2023, 2023 IEEE Conference on Artificial Intelligence (CAI).

Tele-operator performance and their perception of system time lags when completing mobile robot tasks

David A. Sanders, Giles Tewkesbury, Alexander E. Gegov, 2016, 2016 9th International Conference on Human System Interactions (HSI).

Fuzzy Network Based Framework for Software Maintainability Prediction

Xiaowei Wang, Farzad Arabikhan, Qiwei Hu, 2019, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Effect of Nanoparticle and Inclination Angle at Thermal Efficiency in Heatpipes

A. Gegov, R. Jafari, S. Razvarz, 2020, Encyclopedia of Information Science and Technology, Fifth Edition.

Leakage Detection in Pipeline Based on Second Order Extended Kalman Filter Observer

Alexander Gegov, Sina Razvarz, Cristobal Vargas-Jarillo, 2020, Flow Modelling and Control in Pipeline Systems.

Multi-Layer Decision Methodology For Ranking Z-Numbers

Alexander E. Gegov, Ahmad Syafadhli Abu Bakar, A. Gegov, 2015, Int. J. Comput. Intell. Syst..

Integrating fuzzy AHP and Z-TOPSIS for supplier selection in an automotive manufacturing company

Alexander Gegov, Maznah Mat Kasim, Abdul Malek Yaakob, 2019, THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019).

The Application of Z-Numbers in Fuzzy Decision Making: The State of the Art

A. Gegov, N. Jaini, K. Khalif, 2023, Inf..

Fuzzy Differential Equations for Modeling and Control of Fuzzy Systems

Sina Razvarz, Raheleh Jafari, Alexander Gegov, 2018, 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018.

Solving Partial Differential Equations with Bernstein Neural Networks

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2018, UKCI.

Grey Number Based Methodology for Non-homogeneous Preference Elicitation in Fuzzy Risk Analysis Management

Ku Muhammad Naim Ku Khalif, Abdul Malek Yaakob, Alexander Gegov, 2019, Applying Fuzzy Logic for the Digital Economy and Society.

Fuzzy Risk Assessment in the Presence of Uncertainties in Heterogeneous Preferences Elicitation and Reliability

Ahmad Syafadhli Abu Bakar, A. Gegov, K. Khalif, 2021, Industrial Ecology and Environmental Management.

Interval type 2- fuzzy rule based system approach for selection of alternatives using TOPSIS

Alexander E. Gegov, Ku Muhammad Naim Ku Khalif, Siti Fatimah Abdul Rahman, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

Hybrid Intelligent Decision Support System for Drill Rig Performance Analysis and Selection During Well Construction

Catalin Teodoriu, Abdul Malek Yaakob, Alexander Gegov, 2016 .

Improving ability of tele-operators to complete progressively more difficult mobile robot paths using simple expert systems and ultrasonic sensors

David A. Sanders, Alexander E. Gegov, Jasper Graham-Jones, 2010, Ind. Robot.

Power Optimisation Model for Leveraging Cloud System

Mo Adda, Ogechukwu M. Okonor, Alex Gegov, 2019, 2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE).

Intelligent Approach to Minimizing Power Consumption in a Cloud-Based System Collecting Sensor Data and Monitoring the Status of Powered Wheelchairs

David A. Sanders, Mo Adda, Giles Tewkesbury, 2019, IntelliSys.

TrapMP: Malicious Process Detection By Utilising Program Phase Detection

Alexander Gegov, Mo Adda, Zirak Allaf, 2019, 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security).

SPACE-INDEPENDENT COMMUNITY STRUCTURE DETECTION IN UNITED STATES AIR TRANSPORTATION

Fernand Gobet, M. Nadia Postorino, Mark Atherton, 2012 .