MSAFIS: an evolving fuzzy inference system

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

Journal: Soft Computing

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

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.

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

Source: Scopus

MSAFIS: an evolving fuzzy inference system

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

Journal: SOFT COMPUTING

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

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

Source: Web of Science (Lite)

MSAFIS: an evolving fuzzy inference system

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

Journal: Soft Computing

Volume: 21

Issue: 9

Pages: 2357-2366

eISSN: 1433-7479

ISSN: 1432-7643

DOI: 10.1007/s00500-015-1946-4

Abstract:

© 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.

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

Source: Manual

MSAFIS: an evolving fuzzy inference system

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

Journal: Soft Computing

Volume: 21

Issue: 9

Pages: 2357-2366

ISSN: 1432-7643

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.

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

Source: BURO EPrints