A Method of Designing Interpretable Genetic Fuzzy Classification System Based On Mutating Parameters

DOI

10.2991/isrme-15.2015.46How to use a DOI?

Keywords

Fuzzy classification system; Word computing; expertise; mutating parameters

Abstract

This paper discusses the application of generating fuzzy rules with word computing in genetic fuzzy classification system, and proposes a new method to design genetic fuzzy classification system. The new algorithm generates initial fuzzy rules population with expertise of the randomly selecting samples, and adds mutating parameters to adjust the shape of membership function of fuzzy partition in order to expand the algorithm’s search space. Experiments show that the new algorithm has better classification accuracy with shorter length of rules.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hong JI
AU  - Ming Ma
PY  - 2015/04
DA  - 2015/04
TI  - A Method of Designing Interpretable Genetic Fuzzy Classification System Based On Mutating Parameters
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 199
EP  - 202
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.46
DO  - 10.2991/isrme-15.2015.46
ID  - JI2015/04
ER  -