Medical diagnosis applications using a novel interactively recurrent self-evolving fuzzy CMAC model

Jyun Guo Wang, Shen Chuan Tai, Cheng Jian Lin

研究成果: Conference contribution

8 引文 斯高帕斯(Scopus)

摘要

In this paper, a recurrent self-evolving Fuzzy Cerebellar Model Articulation Controller (FCMAC) model for classification problems is developed, namely the interactively recurrent self-evolving fuzzy Cerebellar Model Articulation Controller (IRSFCMAC). The interactively recurrent structure in an IRSFCMAC is formed as external loops and internal feedbacks by feeding the rule firing strength to itself and others rules. The IRSFCMAC learning starts with an empty rule base and all of rules are generated and learned online, through a simultaneous structure and parameter learning, while the relative parameters are learned through a gradient descent algorithm. The proposed IRSFCMAC is tested by the four benchmarked classification problems and compared with the well-known traditional FCMAC. Experimental results show that the proposed IRSFCMAC model enhanced classification performance results, in terms of accuracy and RMSE.

原文English
主出版物標題Proceedings of the International Joint Conference on Neural Networks
發行者Institute of Electrical and Electronics Engineers Inc.
頁面4092-4098
頁數7
ISBN(電子)9781479914845
DOIs
出版狀態Published - 2014 9月 3
事件2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
持續時間: 2014 7月 62014 7月 11

出版系列

名字Proceedings of the International Joint Conference on Neural Networks

Other

Other2014 International Joint Conference on Neural Networks, IJCNN 2014
國家/地區China
城市Beijing
期間14-07-0614-07-11

All Science Journal Classification (ASJC) codes

  • 軟體
  • 人工智慧

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