模糊Kohonen特征映射神经网络及其在成组技术中的应用

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339) Pub Date : 1999-07-10 DOI:10.1109/IJCNN.1999.836057

R. Kuo, S. Chi, B. W. Den

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引用次数: 5

摘要

本文提出了一种新的模糊神经网络，用于零件聚类。该网络具有模糊输入和模糊权重，将Kohonen特征映射神经网络与模糊集理论相结合。模型评价结果表明，与模糊c-means算法和k-means算法相比，所提出的模糊神经网络能提供更准确的决策。

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A fuzzy Kohonen's feature map neural network with application to group technology

This paper proposes a novel fuzzy neural network for clustering the parts into several families. The proposed network, which has fuzzy inputs as well as fuzzy weights, integrates the Kohonen's feature map neural network and the fuzzy set theory. The model evaluation results show that the proposed fuzzy neural network can provide more accurate decision compared to the fuzzy c-means algorithm and k-means algorithm.

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IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)

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