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