https://scholars.lib.ntu.edu.tw/handle/123456789/154264
標題: | Multi-Modal Parameter Identification by Automata Approach | 作者: | Huang, Zen-Kwei SHENG-DE WANG Kuo, Te-Son |
關鍵字: | Learning automata; Multi-modal optimization; Weak law of large number | 公開日期: | 1993 | 卷: | 16 | 期: | 5 | 起(迄)頁: | 603-613 | 來源出版物: | Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an | 摘要: | In this paper, we consider the multi-modal function optimization problem. An automata model with improved learning schemes is proposed to solve the global optimization problem. Theoretically, we prove that theautomaton converges to the global optimum with a probability arbitrarily closeto 1. The numerical simulation results show that the automata approach isbetter than both the well-known gradient approach and the simulated annealing method. The simulation results also show that our automata model converges faster than the other existing models in the literature. © 1993 Taylor & Francis Group, LLC. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/120747 https://www.scopus.com/inward/record.uri?eid=2-s2.0-0027663879&doi=10.1080%2f02533839.1993.9677534&partnerID=40&md5=90e7b89405574f139e4dce9b7dcac8f3 |
ISSN: | 02533839 | DOI: | 10.1080/02533839.1993.9677534 | SDG/關鍵字: | Applications; Mathematical models; Numerical methods; Optimization; Simulation; Automata model; Global optimization; Multi modal function optimization; Automata theory |
顯示於: | 電機工程學系 |
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