Learning technique for TSK fuzzy model based on cooperative

Guo Hui Yang; Qun Wu; Xiao Guang Hu; Yu Jiang

doi:10.1109/ICIEA.2007.4318901

Learning technique for TSK fuzzy model based on cooperative

Guo Hui Yang^*
, Qun Wu
, Xiao Guang Hu
, Yu Jiang

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Harbin Institute of Technology
College of Information and Communication Engineering, Harbin Engineering University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. Fuzzy model is decomposed into two populations: one population describes fuzzy model and its rule construction, and the other population depicts fuzzy partition and membership function parameters. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the technique's validity.

Original language	English
Title of host publication	ICIEA 2007
Subtitle of host publication	2007 Second IEEE Conference on Industrial Electronics and Applications
Pages	2691-2696
Number of pages	6
DOIs	https://doi.org/10.1109/ICIEA.2007.4318901
State	Published - 2007
Event	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 - Harbin, China Duration: 23 May 2007 → 25 May 2007

Publication series

Name	ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

Conference

Conference	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007
Country/Territory	China
City	Harbin
Period	23/05/07 → 25/05/07

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10.1109/ICIEA.2007.4318901

Cite this

@inproceedings{87081cabd3ec46ba93e28ac8a31c5fdd,

title = "Learning technique for TSK fuzzy model based on cooperative",

abstract = "TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. Fuzzy model is decomposed into two populations: one population describes fuzzy model and its rule construction, and the other population depicts fuzzy partition and membership function parameters. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the technique's validity.",

author = "Yang, \{Guo Hui\} and Qun Wu and Hu, \{Xiao Guang\} and Yu Jiang",

year = "2007",

doi = "10.1109/ICIEA.2007.4318901",

language = "英语",

isbn = "1424407370",

series = "ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications",

pages = "2691--2696",

booktitle = "ICIEA 2007",

note = "2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 ; Conference date: 23-05-2007 Through 25-05-2007",

}

Yang, GH, Wu, Q, Hu, XG & Jiang, Y 2007, Learning technique for TSK fuzzy model based on cooperative. in ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications., 4318901, ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications, pp. 2691-2696, 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, Harbin, China, 23/05/07. https://doi.org/10.1109/ICIEA.2007.4318901

Learning technique for TSK fuzzy model based on cooperative. / Yang, Guo Hui; Wu, Qun; Hu, Xiao Guang et al.
ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications. 2007. p. 2691-2696 4318901 (ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Yang, Guo Hui

AU - Wu, Qun

AU - Hu, Xiao Guang

AU - Jiang, Yu

PY - 2007

Y1 - 2007

N2 - TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. Fuzzy model is decomposed into two populations: one population describes fuzzy model and its rule construction, and the other population depicts fuzzy partition and membership function parameters. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the technique's validity.

AB - TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. Fuzzy model is decomposed into two populations: one population describes fuzzy model and its rule construction, and the other population depicts fuzzy partition and membership function parameters. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the technique's validity.

UR - https://www.scopus.com/pages/publications/35248847412

U2 - 10.1109/ICIEA.2007.4318901

DO - 10.1109/ICIEA.2007.4318901

M3 - 会议稿件

AN - SCOPUS:35248847412

SN - 1424407370

SN - 9781424407378

T3 - ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

SP - 2691

EP - 2696

BT - ICIEA 2007

T2 - 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007

Y2 - 23 May 2007 through 25 May 2007

ER -

Learning technique for TSK fuzzy model based on cooperative

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