TY - GEN
T1 - Sparse fuzzy c-regression models with application to T-S fuzzy systems identification
AU - Luo, Minnan
AU - Sun, Fuchun
AU - Liu, Huaping
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/4
Y1 - 2014/9/4
N2 - In this paper, the objective function of fuzzy c-regression models (FCRM) is modified to develop a novel fuzzy partition method on the basis of block structured sparse representation, namely as sparse fuzzy c-regression model. This method takes advantage of the block structured information in the objective function of FCRM and casts fuzzy partition into an optimization problem by making a tradeoff between traditional FCRM and the number of prototypes of hyper-plane with nonzero parameters. An alternating direction method of multipliers (ADMM) based algorithm is exploited to address the proposed optimization problem. Furthermore, based on sparse fuzzy c-regression models, a novel T-S fuzzy systems identification method is developed for reduction of fuzzy rules. Finally, examples on well-known benchmark data set are carried out to illustrate the effectiveness of the proposed methods.
AB - In this paper, the objective function of fuzzy c-regression models (FCRM) is modified to develop a novel fuzzy partition method on the basis of block structured sparse representation, namely as sparse fuzzy c-regression model. This method takes advantage of the block structured information in the objective function of FCRM and casts fuzzy partition into an optimization problem by making a tradeoff between traditional FCRM and the number of prototypes of hyper-plane with nonzero parameters. An alternating direction method of multipliers (ADMM) based algorithm is exploited to address the proposed optimization problem. Furthermore, based on sparse fuzzy c-regression models, a novel T-S fuzzy systems identification method is developed for reduction of fuzzy rules. Finally, examples on well-known benchmark data set are carried out to illustrate the effectiveness of the proposed methods.
UR - https://www.scopus.com/pages/publications/84912531152
U2 - 10.1109/FUZZ-IEEE.2014.6891567
DO - 10.1109/FUZZ-IEEE.2014.6891567
M3 - 会议稿件
AN - SCOPUS:84912531152
T3 - IEEE International Conference on Fuzzy Systems
SP - 1571
EP - 1577
BT - Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
Y2 - 6 July 2014 through 11 July 2014
ER -