FFAネットワーク推論システムの学習法と応用事例

概要

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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.
バイオメディカル・ファジィ・システム学会の論文
1992-05-07