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An Efficient Algorithm to Computing Max–Min Inverse Fuzzy Relation for Abductive Reasoning

机译:用于归纳推理的最大-最小逆模糊关系的高效算法

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This paper provides an alternative formulation to computing the max-min inverse fuzzy relation by embedding the inherent constraints of the problem into a heuristic (objective) function. The optimization of the heuristic function guarantees maximal satisfaction of the constraints, and consequently, the condition for optimality yields solution to the inverse problem. An algorithm for computing the max-min inverse fuzzy relation is proposed. An analysis of the algorithm indicates its relatively better computational accuracy and higher speed in comparison to the existing technique for inverse computation. The principle of fuzzy abduction is extended with the proposed inverse formulation, and the better relative accuracy of the said abduction over existing works is established through illustrations with respect to a predefined error norm.
机译:本文通过将问题的固有约束嵌入启发式(目标)函数中,提供了一种计算最大-最小逆模糊关系的替代公式。启发式函数的优化保证了约束的最大满足,因此,最优性条件产生了反问题的解。提出了最大-最小逆模糊关系的计算算法。对算法的分析表明,与现有的逆计算技术相比,该算法具有更好的计算精度和更高的速度。通过采用提出的逆公式扩展了模糊绑架的原理,并且通过关于预定义的误差范数的图示,建立了所述绑架相对于现有作品的更好的相对准确性。

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