A Novel Interactively Recurrent Self-evolving Fuzzy CMAC and Its Classification Applications

NCUTIR > College of Electrical Engineering and Computer Science > Department of Computer Science and Information Engineering > 【資訊工程系所】期刊論文 > Item 987654321/5969

Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/5969

Title:	A Novel Interactively Recurrent Self-evolving Fuzzy CMAC and Its Classification Applications
Authors:	Jyun-Guo Wang, Shen-Chuan Tai, Cheng-Jian Lin
Contributors:	圖書館
Keywords:	Recurrent network cerebellar model articulation controller fuzzy theory gradient descent algorithm classification
Date:	2015-09
Issue Date:	2016-10-20 15:36:31 (UTC+8)
Abstract:	In this paper, an Interactively Recurrent Self-evolving Fuzzy Cerebellar Model Articulation Controller (IRSFCMAC) model is developed for solving classification problems. The proposed IRSFCMAC classifier consists of internal feedback and external loops, which are generated by the hypercube cell firing strength to itself and other hypercube cells. The learning process of the IRSFCMAC gets started with an empty hypercube base, and then all of hypercube cells are generated and learned online via structure and parameter learning, respectively. The structure learning algorithm is based on the degree measure to determine the number of hypercube cells. The parameter learning algorithm, based on the gradient descent method, adjusts the shapes of the membership functions and the corresponding fuzzy weights of the IRSFCMAC. Finally, the proposed IRSFCMAC model is tested by four benchmark classification problems. Experimental results show that the proposed IRSFCMAC model has superior performance than traditional FCMAC and other models.
Relation:	International Journal of Computational Intelligence and Applications, Volume 14, Issue 03
Appears in Collections:	[Department of Computer Science and Information Engineering] 【資訊工程系所】期刊論文

Files in This Item:

There are no files associated with this item.

View Licence

Loading...