MSAFIS: an evolving fuzzy inference system

Authors: de Jesús Rubio, J. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/29408/

Journal: Soft Computing

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

© 2015, Springer-Verlag Berlin Heidelberg.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.

This data was imported from Scopus:

Authors: de Jesús Rubio, J. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/29408/

Journal: Soft Computing

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

© 2015, Springer-Verlag Berlin Heidelberg. 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.

This source preferred by Hamid Bouchachia

This data was imported from Web of Science (Lite):

Authors: de Jesus Rubio, J. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/29408/

Journal: SOFT COMPUTING

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

The data on this page was last updated at 04:42 on September 24, 2017.