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Soft Computing
Published in: Soft Computing 9/2017

19-11-2015 | Methodologies and Application

MSAFIS: an evolving fuzzy inference system

Authors: José de Jesús Rubio, Abdelhamid Bouchachia

Published in: Soft Computing | Issue 9/2017

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Abstract

In this paper, the problem of learning in big data is considered. To solve this problem, a new algorithm is proposed as the combination of two important evolving and stable intelligent algorithms: the sequential adaptive fuzzy inference system (SAFIS), and stable gradient descent algorithm (SGD). The modified sequential adaptive fuzzy inference system (MSAFIS) is the SAFIS with the difference that the SGD is used instead of the Kalman filter for the updating of parameters. The SGD improves the Kalman filter, because it first obtains a better learning in big data. The effectiveness of the introduced method is verified by two experiments.
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Metadata
Title
MSAFIS: an evolving fuzzy inference system
Authors
José de Jesús Rubio
Abdelhamid Bouchachia
Publication date
19-11-2015
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 9/2017
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-015-1946-4

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