International Journal of Computational Intelligence Systems

Volume 5, Issue 2, April 2012, Pages 322 - 342

Improving Transparency in Approximate Fuzzy Modeling Using Multi-objective Immune-Inspired Optimisation

Authors
Jun Chen, Mahdi Mahfouf
Corresponding Author
Jun Chen
Received 11 November 2010, Accepted 1 June 2011, Available Online 1 April 2012.
DOI
10.1080/18756891.2012.685311How to use a DOI?
Keywords
Interpretability, Immune-inspired multi-objective optimisation, Variable length coding scheme
Abstract

In this paper, an immune inspired multi-objective fuzzy modeling (IMOFM) mechanism is proposed specifically for high-dimensional regression problems. For such problems, prediction accuracy is often the paramount requirement. With such a requirement in mind, however, one should also put considerable efforts in eliciting models which are as transparent as possible, a ‘tricky’ exercise in itself. The proposed mechanism adopts a multi-stage modeling procedure and a variable length coding scheme to account for the enlarged search space due to simultaneous optimisation of the rule-base structure and its associated parameters. We claim here that IMOFM can account for both Singleton and Mamdani Fuzzy Rule-Based Systems (FRBS) due to the carefully chosen output membership functions, the inference scheme and the defuzzification method. The proposed modeling approach has been compared to other representatives using a benchmark problem, and was further applied to a high-dimensional problem, taken from the steel industry, which concerns the prediction of mechanical properties of hot rolled steels. Results confirm that IMOFM is capable of eliciting not only accurate but also transparent FRBSs from quantitative data.

Copyright
© 2017, 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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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
5 - 2
Pages
322 - 342
Publication Date
2012/04/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2012.685311How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - JOUR
AU  - Jun Chen
AU  - Mahdi Mahfouf
PY  - 2012
DA  - 2012/04/01
TI  - Improving Transparency in Approximate Fuzzy Modeling Using Multi-objective Immune-Inspired Optimisation
JO  - International Journal of Computational Intelligence Systems
SP  - 322
EP  - 342
VL  - 5
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.685311
DO  - 10.1080/18756891.2012.685311
ID  - Chen2012
ER  -