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Robustness of full implication algorithms based on interval-valued fuzzy inference

机译:基于区间值模糊推理的全蕴涵算法的鲁棒性

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In this paper, a new full implication algorithm based on interval-valued fuzzy inference which extends the triple I principle for fuzzy inference based on fuzzy modus ponens and fuzzy modus tollens to the case of interval-valued fuzzy sets is presented. We first give the corresponding interval-valued R-type triple I solutions and then investigate the robustness of triple I algorithms based on interval-valued fuzzy sets for fuzzy inference. The sensitivity of some special algorithms based on four important interval-valued residuated implication is given. It is shown that the robustness of interval-valued full implication algorithms for fuzzy inference directly depends on the selection of interval-valued fuzzy connectives. (C) 2015 Elsevier Inc. All rights reserved.
机译:本文提出了一种新的基于区间值模糊推理的全蕴涵算法,将基于模糊模态和模糊模态收费的模糊推理的三重I原理扩展到区间值模糊集的情况。我们首先给出相应的区间值R型三I解,然后研究基于区间值模糊集的三I算法的鲁棒性。给出了一些基于四个重要的区间值剩余蕴涵的特殊算法的敏感性。结果表明,区间值全蕴涵算法对模糊推理的鲁棒性直接取决于区间值模糊连词的选择。 (C)2015 Elsevier Inc.保留所有权利。

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