基于模糊知识库的快速推理神经网络

[1992] Proceedings. The Sixteenth Annual International Computer Software and Applications Conference Pub Date : 1992-09-21 DOI:10.1109/CMPSAC.1992.217577

K. S. Kumar, M. Sparancia, A. Unnikrishnan

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摘要

作者讨论了一个框架，该框架可以使用神经网络从模糊的示例知识库中进行快速推理。他们提出了一种方案，利用一对模糊项之间的特征调整相似性度量将示例库解模糊化为一组相似性向量，然后用这些相似性向量训练神经网络。采用带反向传播学习规则的多层前馈神经网络。

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A neural network for fast inferencing on a fuzzy knowledge base

The authors discuss a framework where fast inferences could be made from a fuzzy knowledge base of examples using neural networks. They sketch a scheme for defuzzifying the example base into a set of similarity vectors using a trait-adjusted similarity measure between a pair of fuzzy terms, and then training a neural network with these similarity vectors. A multilayer feedforward neural network with backpropagation learning rule was used.<>

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[1992] Proceedings. The Sixteenth Annual International Computer Software and Applications Conference

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