一种考虑数据结构的融合轴模糊建模方法

Kosuke Yamamoto, T. Yoshikawa, T. Furuhashi
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引用次数: 5

摘要

模糊建模是识别未知非线性输入输出关系的有效方法之一。在从已构建的模型中收集信息或从已知信息中构建模型时,模型的可理解性变得至关重要。本文通过拟合输入空间中的分布式数据来定义新的轴,并提出了一种考虑数据结构的模糊建模方法。本文称这些轴为“融合轴”。数值实验表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A proposal of fuzzy modeling on fusion axes considering the data structure
Fuzzy modeling is known as one of the effective methods to identify unknown non-linear input-output relationships. In gathering information from constructed models or constructing models from known information, the model's understandability becomes essential. This paper defines new axes by fitting distributed data in input space and proposes a fuzzy modeling method considering data structure. This paper calls these axes, "fusion axes". The effectiveness of the proposed method is shown through some numerical experiments.
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