Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm

Eugene Semenkin; Vladimir Stanovov

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Paper

Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm

Topics: Evolutionary Computation and Control; Hybrid Learning Systems; Machine Learning in Control Applications

In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, 318-323, 2014 , Vienna, Austria

Authors: Eugene Semenkin and Vladimir Stanovov

Affiliation: Siberian State Aerospace University, Russian Federation

Keyword(s): Genetic Fuzzy Systems, Fuzzy Rule Base Classifiers, Automated Design, Evolutionary Algorithms.

Related Ontology Subjects/Areas/Topics: Evolutionary Computation and Control ; Hybrid Learning Systems ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications

Abstract: Self-configuring evolutionary algorithm of fuzzy rule bases automated deign for solving classification problems, which combines Pittsburgh and Michigan approaches, is introduced. The evolutionary algorithm is based on the Pittsburgh approach where every individual is a rule base and the Michigan approach is used as a mutation operator. A self-configuration method is used to adjust probabilities of the usage of selection, mutation and Michigan part operators. Testing the algorithm on a number of real-world problems demonstrates its efficiency comparing to several other commonly used approaches.

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Paper citation in several formats:

Semenkin, E. and Stanovov, V. (2014). Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm. In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-039-0; ISSN 2184-2809, SciTePress, pages 318-323. DOI: 10.5220/0005062003180323

@conference{icinco14,
author={Eugene Semenkin and Vladimir Stanovov},
title={Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2014},
pages={318-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005062003180323},
isbn={978-989-758-039-0},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm
SN - 978-989-758-039-0
IS - 2184-2809
AU - Semenkin, E.
AU - Stanovov, V.
PY - 2014
SP - 318
EP - 323
DO - 10.5220/0005062003180323
PB - SciTePress