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An improvement to Koczy's interpolative reasoning method based on Taylor progression

机译:基于泰勒级数的Koczy插值推理方法的改进

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In the sparse fuzzy rules, the reasoning consequence cannot be obtained by the traditional fuzzy reasoning method. To tackle this problem, Koczy and Hirota have proposed a linear interpolative reasoning method. This method resolved the problem of how to derive the reasoning consequence in the sparse fuzzy rules, but the reasoning consequences by this method sometimes become abnormal fuzzy sets [Y. Shi et al., 1995; Y. Shi & M. Mizumoto, 1997]. In order to guarantee "if fuzzy rules A/sub 1//spl ges/B/sub 1/, A/sub 2//spl ges/B/sub 2/ and the observation A* are defined by triangular membership functions, then the interpolated conclusion B* is linearity and convexity", we shall propose the interpolative method based on Taylor progression.
机译:在稀疏的模糊规则中,传统的模糊推理方法无法获得推理结果。为了解决这个问题,Koczy和Hirota提出了一种线性插值推理方法。这种方法解决了在稀疏模糊规则中如何推导推理结果的问题,但是这种方法的推理结果有时会变成异常的模糊集[Y. Shi et al。,1995; J.Am.Chem.Soc。,1995; 5(1):1,4。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。 Y. Shi&M. Mizumoto,1997年]。为了保证“如果模糊规则A / sub 1 // spl ges / B / sub 1 /,A / sub 2 // spl ges / B / sub 2 /和观测值A *由三角隶属函数定义,则内插结论B *是线性和凸”,我们将提出基于泰勒级数的内插方法。

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