T-S fuzzy model identification based on improved interval type-2 fuzzy c-means clustering algorithm

Shuai Cao; Chenguang Qiu; Chaojie Ding; Yaou Wang

doi:10.1117/12.2667629

22 February 2023 T-S fuzzy model identification based on improved interval type-2 fuzzy c-means clustering algorithm

Shuai Cao, Chenguang Qiu, Chaojie Ding, Yaou Wang

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 1258726 (2023) https://doi.org/10.1117/12.2667629
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

In according with nonlinear identification problem, an improved interval type-2 fuzzy c-mean clustering algorithm is proposed. A novel objective function is adapted in improved interval type-2 fuzzy c-mean clustering algorithm, which can reduce the influence of noise on clustering results. The proposed clustering algorithm is applied to T-S fuzzy model premise parameters identification and least squares is used for consequent parameters identification. The proposed identification algorithm is applied to double input single output model and actual thermal power unit main steam temperature data model, the identification results show that, the proposed algorithm has higher identification accuracy.

Citation Download Citation

Shuai Cao, Chenguang Qiu, Chaojie Ding, and Yaou Wang "T-S fuzzy model identification based on improved interval type-2 fuzzy c-means clustering algorithm", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 1258726 (22 February 2023); https://doi.org/10.1117/12.2667629

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