TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms

Cosmin Danut Bocaniala; José Sa da Costa

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Paper

TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms

Topics: Intelligent Fault Detection and Identification

In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, 157-162, 2004 , Setúbal, Portugal

Authors: Cosmin Danut Bocaniala ¹ and José Sa da Costa ²

Affiliations: ¹ “Dunarea de Jos” University, Romania ; ² Technical University of Lisbon, Portugal

Keyword(s): Particle swarm optimization, Parameters, Fault diagnosis, Pattern recognition, Fuzzy logic.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Intelligent Fault Detection and Identification

Abstract: This paper presents a comparison between the use of particle swarm optimization and the use of genetic algorithms for tuning the parameters of a novel fuzzy classifier. In previous work on the classifier, the large amount of time needed by genetic algorithms has been significantly diminished by using an optimized initial population. Even with this improvement, the time spent on tuning the parameters is still very large. The present comparison suggests that using particle swarm optimization may improve considerably the time needed for tuning the parameters. In this way, the fuzzy classifier becomes suitable for real world application. The result is validated by application to a fault diagnosis benchmark.

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Paper citation in several formats:

Bocaniala, C. and Costa, J. (2004). TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms. In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 972-8865-12-0; ISSN 2184-2809, SciTePress, pages 157-162. DOI: 10.5220/0001143801570162

@conference{icinco04,
author={Cosmin Danut Bocaniala. and José Sa da Costa.},
title={TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2004},
pages={157-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001143801570162},
isbn={972-8865-12-0},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - TUNING THE PARAMETERS OF A CLASSIFIER FOR FAULT DIAGNOSIS - Particle Swarm Optimization vs Genetic Algorithms
SN - 972-8865-12-0
IS - 2184-2809
AU - Bocaniala, C.
AU - Costa, J.
PY - 2004
SP - 157
EP - 162
DO - 10.5220/0001143801570162
PB - SciTePress