Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm

Eugene Semenkin, Vladimir Stanovov

2014

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.

Paper Citation

in Harvard Style

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 1: ICINCO, ISBN 978-989-758-039-0, pages 318-323. DOI: 10.5220/0005062003180323

in Bibtex Style

@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 1: ICINCO,},
year={2014},
pages={318-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005062003180323},
isbn={978-989-758-039-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Fuzzy Rule Bases Automated Design with Self-configuring Evolutionary Algorithm
SN - 978-989-758-039-0
AU - Semenkin E.
AU - Stanovov V.
PY - 2014
SP - 318
EP - 323
DO - 10.5220/0005062003180323