Genetic fuzzy logic controllers

Yu-Chiun Chiou*, Lawrence W. Lan

*此作品的通信作者

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

The conventional fuzzy logic controller (CFLC) Is limited In application, because its logic rules and membership functions have to be preset with expert knowledge. To avoid such drawbacks, a genetic fuzzy logic controller (GFLC) is proposed by employing an Iterative evolution algorithm to promote the learning performance of logic rules and the tuning effectiveness or membership functions from examples in sequence. In addition, an encoding method is developed to overcome the difficulties in dealing with numerous constraints while employing genetic algorithms in tuning membership functions. A case of GM car-following behavior is experimented to verify the applicability and robustness of GFLC. The results demonstrate that GFLC can predict the car-following behaviors precisely. Due to the similarity between fuzzy neural networks (FNN) and GFLC, a comparison is also made and the results indicate that GFLC performs superior to FNN.

原文English
主出版物標題IEEE 5th International Conference on Intelligent Transportation Systems, ITSC 2002 - Proceedings
編輯Der-Horng Lee, Dipti Srinivasan, Ruey Long Cheu
發行者Institute of Electrical and Electronics Engineers Inc.
頁面200-205
頁數6
ISBN(電子)0780373898
DOIs
出版狀態Published - 1 1月 2002
事件5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002 - Singapore, Singapore
持續時間: 3 9月 20026 9月 2002

出版系列

名字IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
2002-January

Conference

Conference5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002
國家/地區Singapore
城市Singapore
期間3/09/026/09/02

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