Applying SOM as a search mechanism for dynamic system

Yi Yuan Chen, Kuu-Young Young

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)

摘要

The self-organizing map (SOM), as a kind of unsupervised neural network, has been applied for both static data management and dynamic data analysis. To further exploit Its ability in search, in this paper, we employ the SOM as a searching mechanism for dynamic system. A learning scheme, consisting mainly of the SOM and the target dynamic system, Is then proposed. The performance of this SOM-based learning scheme is especially compared with that of the genetic algorithm (GA) due to their resemblance in learning and searching. And, a new SOM weight updating rule Is proposed to enhance learning efficiency, which may dynamically adjust the neighborhood function for the SOM in learning system parameters. For demonstration, the proposed learning scheme is applied for trajectory prediction, and Its effectiveness evaluated via the simulations based on using the SOM, GA, and also Kalman filtering.

原文English
主出版物標題Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
頁面4111-4116
頁數6
DOIs
出版狀態Published - 1 十二月 2005
事件44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 - Seville, Spain
持續時間: 12 十二月 200515 十二月 2005

出版系列

名字Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
2005

Conference

Conference44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
國家Spain
城市Seville
期間12/12/0515/12/05

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