度量空间中的规则近似

2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2010-03-04 DOI:10.1109/SAMI.2010.5423702

L. Kovács

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引用次数: 13

摘要

经典的模糊规则插值器在欧几里德空间中工作，在欧几里德空间中，新的模糊值可以由训练值生成。本文研究了在一般度量空间上定义模糊值的情况。在这种情况下，使用分类过程来近似请求的值。本文介绍了该分类过程的基本方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Rule approximation in metric spaces

The classical fuzzy rule interpolators work in Euclidean spaces where the new fuzzy value can be generated from the training values. The paper investigates the case when the fuzzy values are defined over the general metric spaces. In this case a classification process is used to approximate the requested value. The paper introduces a base method for this classification process.

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来源期刊

2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI)

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