Proceedings of the Annual Meeting of Biomedical Fuzzy Systems Association : BMFSA
Online ISSN : 2433-1449
会議情報
FFAネットワーク推論システムの学習法と応用事例
徳永 雅彦河野 かほる橋詰 義晴浜谷 和彦渡辺 正明中村 健上石 陽一
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会議録・要旨集 フリー

p. 173-182

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We propose a new Neural Network (NN) system named Fuzzy Filtered Synapse (FFS) by which information is filtered actively by fuzzy membership function before input to Synapse. With the FFS-Network complicated and/or vague problems can be resolved easily, since non-linear and non-monotonic fuzzy membership functions are learned directly and the network is organized automatically. The usefulness of FFS has been confirmed through some applications. In this paper, we introduce an application to a scheduling problem of menu. In the learning, an example of menu list made by a dietitian is given to the network, and filter functions and weights of each synapse are determined. From the result of reasoning that all generated menu lists with various restrictions satisfy adequate balance, it has been confirmed that the network can learn the hidden knowhow of menu ordering.

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© 1992 Biomedical Fuzzy Systems Association
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