International Journal of Computational Intelligence Systems

Volume 12, Issue 1, November 2018, Pages 108 - 122

Multi-Scale Fuzzy Feature Selection Method applied to Wood Singularity Identification

Authors
Vincent BOMBARDIER1, vincent.bombardier@univ-lorraine.fr, Laurent WENDLING2, lwendlin@math-info.univ-paris5.fr
1Université de Lorraine, CNRS, CRAN, F-54000, France
2Université Paris Descartes, LIPADE, Sorbonne Paris Cité 75270 Paris Cedex 06
Corresponding Author
Vincent Bombardier
Received 23 March 2018, Accepted 16 September 2018, Available Online 1 November 2018.
DOI
https://doi.org/10.2991/ijcis.2018.25905185How to use a DOI?
Keywords
Image processing, Fuzzy logic, Pattern recognition, Feature selection, Choquet integral
Abstract

A multi-scale feature selection method based on the Choquet Integral is presented in this paper. Usually, aggregation decision-making problems are well solved, relying on few decision rules associated to a small number of input parameters. However, many industrial applications require the use of numerous features although not all of them will be relevant. Thus, a new feature selection model is proposed to achieve a suitable set of input features while reducing the complexity of the decision-making problem. First, a new criterion, combining the importance of the parameters as well as their interaction indices is defined to sort them out by increasing impact. Then, this criterion is embedded into a new random parameter space partitioning algorithm. Last, this new feature selection method is applied to an industrial wood singularity identification problem. The experimental study is based on the comparative analysis of the results obtained from the process of selecting parameters in several feature selection methods. The experimental study attests to the relevance of the remaining set of selected parameters.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 1
Pages
108 - 122
Publication Date
2018/11
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2018.25905185How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Vincent Bombardier
AU  - Laurent Wendling
PY  - 2018
DA  - 2018/11
TI  - Multi-Scale Fuzzy Feature Selection Method applied to Wood Singularity Identification
JO  - International Journal of Computational Intelligence Systems
SP  - 108
EP  - 122
VL  - 12
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2018.25905185
DO  - https://doi.org/10.2991/ijcis.2018.25905185
ID  - Bombardier2018
ER  -