Alexander E. Gegov

发表

Learning to Make Intelligent Decisions Using an Expert System for the Intelligent Selection of Either PROMETHEE II or the Analytical Hierarchy Process

Malik Haddad, David A. Sanders, Nils Bausch, 2018, IntelliSys.

Fuzzy networks with feedback rule bases for complex systems modelling

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

Dynamic Resource Allocation Through Workload Prediction for Energy Efficient Computing

Alexander E. Gegov, Adeel Ahmed, David J. Brown, 2016, UKCI.

Genetic Algorithm Modeling for Photocatalytic Elimination of Impurity in Wastewater

Alexander E. Gegov, Wen Yu, Morten Goodwin Olsen, 2019, IntelliSys.

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

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

Generalised Fuzzy Bayesian Network with Adaptive Vectorial Centroid

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

The Effect of Baffles on Heat Transfer

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

Flow Modelling and Control in Pipeline Systems - A Formal Systematic Approach

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2021 .

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.

Modeling and Control of Uncertain Nonlinear Systems

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

Parallel Distributed Compensation for Voltage Controlled Active Magnetic Bearing System using Integral Fuzzy Model

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

Making Decisions About Saving Energy in Compressed Air Systems Using Ambient Intelligence and Artificial Intelligence

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

Application of Deep Learning for the Diagnosis of Cardiovascular Diseases

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

Intelligent modelling of the indoor climate in buildings by soft computing

Alexander E. Gegov, 2001, EUSFLAT Conf..

Fast Transformations to Provide Simple Geometric Models of Moving Objects

David A. Sanders, Giles Tewkesbury, Alexander E. Gegov, 2015, ICIRA.

Validation of methods for ranking fuzzy numbers in decision making

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

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.

Guest Editorial: Deep Fuzzy Models

Alexander E. Gegov, João Miguel da Costa Sousa, Uzay Kaymak, 2020, IEEE Trans. Fuzzy Syst..

A New Computational Method for Solving Fully Fuzzy Nonlinear Systems

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

Complexity management methodology for fuzzy systems with feedback rule bases

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

End-to-End Memory Networks: A Survey

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2020, SAI.

Fuzzy Networks for Complex Systems - A Modular Rule Base Approach

Alexander E. Gegov, 2010, Studies in Fuzziness and Soft Computing.

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.

Advanced modelling of complex processes by rule based networks

Alexander E. Gegov, Nedyalko Petrov, Boriana Vatchova, 2010, 2010 5th IEEE International Conference Intelligent Systems.

Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS

Alexander E. Gegov, Mohamed Bader-El-Den, Siti Fatimah Abdul Rahman, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

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).

Solution of Dual Fuzzy Equations Using a New Iterative Method

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

Filtration of Non-Monotonic Rules for Fuzzy Rule Base Compression

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

Linguistic composition based modelling by fuzzy networks with modular rule bases

Alexander E. Gegov, Nedyalko Petrov, Farzad Arabikhan, 2015, Fuzzy Sets Syst..

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).

Selection of alternatives using fuzzy networks with rule base aggregation

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

Multilayer fuzzy control of multivariable systems by active decomposition

Alexander E. Gegov, 1997, Int. J. Intell. Syst..

Mamdani fuzzy networks with feedforward rule bases for complex systems modelling

David A. Sanders, Alexander E. Gegov, Boriana Vatchova, 2016, J. Intell. Fuzzy Syst..

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

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

Fuzzy rule based networks

Alexander E. Gegov, 2011, 2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI).

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).

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..

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..

Ranking of fuzzy numbers based on centroid point and spread

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

Collaborative rule generation: An ensemble learning approach

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

Rule base simplification in fuzzy systems by aggregation of inconsistent rules

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

Combining Multiple Criteria Decision Making with Vector Manipulation to Decide on the Direction for a Powered Wheelchair

Malik Haddad, David A. Sanders, Alexander E. Gegov, 2019, IntelliSys.

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..

Advanced Inference in Fuzzy Systems by Rule Base Compression

Alexander E. Gegov, Neelamugilan Gobalakrishnan, 2007, EUSFLAT Conf..

Advances in fuzzy systems and networks

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

Introducing dead bands within two-dimensional clusters of user data to improve data classification

David A. Sanders, Alexander E. Gegov, Jorge Bergasa-Suso, 2016, 2016 9th International Conference on Human System Interactions (HSI).

Rule base identification in fuzzy networks by Boolean matrix equations

Alexander E. Gegov, Nedyalko Petrov, Emil Gegov, 2014, J. Intell. Fuzzy Syst..

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..

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.

Categorization and Construction of Rule Based Systems

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

Multi-Layer Decision Methodology For Ranking Z-Numbers

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

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).

ConfMVM: A Hardware-Assisted Model to Confine Malicious VMs

Alexander E. Gegov, Mo Adda, Zirak Allaf, 2018, 2018 UKSim-AMSS 20th International Conference on Computer Modelling and Simulation (UKSim).

Initial Results from Using Preference Ranking Organization Methods for Enrichment of Evaluations to Help Steer a Powered Wheelchair

Malik Haddad, David A. Sanders, Alexander E. Gegov, 2019, IntelliSys.

Boolean matrix equations for node identification in fuzzy rule based networks

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

Modular rule base fuzzy networks for linguistic composition based modelling

David A. Sanders, Alexander E. Gegov, Nedyalko Petrov, 2017, Int. J. Knowl. Based Intell. Eng. 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).

Complexity management methodology for fuzzy systems with feedforward rule bases

David A. Sanders, Alexander E. Gegov, Boriana Vatchova, 2015, Int. J. Knowl. Based Intell. Eng. Syst..

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

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

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).

Solving Partial Differential Equations with Bernstein Neural Networks

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

A Comparison Study on Flush+Reload and Prime+Probe Attacks on AES Using Machine Learning Approaches

Alexander E. Gegov, Mo Adda, Zirak Allaf, 2017, UKCI.

Sharing Driving Between a Vehicle Driver and a Sensor System Using Trust-Factors to Set Control Gains

David A. Sanders, Alexander E. Gegov, Rinat Khusainov, 2018, IntelliSys.

Applications of Z-Numbers and Neural Networks in Engineering

Alexander E. Gegov, Sina Razvarz, Raheleh Jafari, 2020, SAI.

Decision making problem solving using fuzzy networks with rule base aggregation

Alexander E. Gegov, Siti Fatimah Abdul Rahman, Abdul Malek Yaakob, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Expert system to interpret hand tremor and provide joystick position signals for powered wheelchairs with ultrasonic sensor systems

David A. Sanders, Giles Tewkesbury, Alexander E. Gegov, 2011, Ind. Robot.

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).

Complexity Management in Fuzzy Systems - A Rule Base Compression Approach

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

Multilayer fuzzy control of multivariable systems by direct decomposition

Alexander E. Gegov, 1998, Int. J. Syst. Sci..

Fuzzy rule based approach with z-numbers for selection of alternatives using TOPSIS

Alexander E. Gegov, Abdul Malek Yaakob, A. Gegov, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

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).

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).

Complexity Control in Rule Based Models for Classification in Machine Learning Context

Han Liu, Alexander E. Gegov, Mihaela Cocea, 2016, UKCI.

Knowledge extraction methods for complex processes operating under uncertainty

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

Intuition based Decision Methodology for Ranking Interval Type - II Fuzzy Numbers

Alexander E. Gegov, Ahmad Syafadhli Abu Bakar, 2015, IFSA-EUSFLAT.

Post Processing Method that Acts on Two-dimensional Clusters of User Data to Produce Dead Bands and Improve Classification

David A. Sanders, Alexander E. Gegov, 2015, WEBIST.

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.

Facial Recognition Software for Identification of Powered Wheelchair Users

Malik Haddad, Giles Tewkesbury, Alexander E. Gegov, 2021, IntelliSys.

Are Human Drivers a Liability or an Asset?

Malik Haddad, Giles Tewkesbury, Alexander E. Gegov, 2021, IntelliSys.

Light Syntax Parsing and Fuzzy Systems for Rhetorical Structure Theory Text Segmentation

Alexander E. Gegov, Rinat Khusainov, Ella Haig, 2021, 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

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.