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Knowledge reasoning approach with linguistic-valued intuitionistic fuzzy credibility

机译:具有语言价值的直觉模糊可信度的知识推理方法

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摘要

Linguistic term evaluations are always collected from two opposite sides at the same time in an assessment system. To process the linguistic knowledge, we propose an approximate reasoning approach with linguistic-valued intuitionistic fuzzy credibility based on linguistic-valued intuitionistic fuzzy lattice implication algebra and apply it to the assessment system. Firstly, we give a knowledge representation model with linguistic-valued intuitionistic fuzzy credibility. Based on the representation model, the forms and patterns of linguistic intuitionistic fuzzy modus ponens (LI-FMP) and linguistic intuitionistic fuzzy modus tollens (LI-FMT) are defined. Then there are three main phases of the knowledge reasoning with linguistic-valued intuitionistic fuzzy credibility. For a single rule, the similarity-based algorithms for LI-FMP and LI-FMT are given to get the sub-conclusion and the properties of similarity-based algorithms are discussed. For the multi-rule, we propose a rule aggregation operator to get the final conclusion by combining all the sub-conclusions. Some incomparable results are further processed if it is necessary. An intuitionistic linguistic-real valuation function is defined implying a linguistic intuitionistic fuzzy distance which is proved to be a positive valuation function. The ranking method of the incomparable results utilizes the linguistic intuitionistic distance. Lastly, the example about individual credit risk assessment shows how the proposed approach work and the contrast example illustrates that the proposed approach is rational and applied.
机译:语言术语评估始终在评估系统中同时从两个相对的方面进行收集。为了处理语言知识,我们提出了一种基于语言价值直觉模糊格蕴涵代数的具有语言价值直觉模糊可信度的近似推理方法,并将其应用于评估系统。首先,给出了具有语言价值的直觉模糊可信度的知识表示模型。基于表示模型,定义了语言直觉模糊模态量词(LI-FMP)和语言直觉模糊模态量词(LI-FMT)的形式和模式。然后,具有语言价值的直觉模糊可信度的知识推理分为三个主要阶段。对于单个规则,给出了基于相似度的LI-FMP和LI-FMT算法,以得出子结论,并讨论了基于相似度的算法的性质。对于多规则,我们提出了一个规则聚合算子,通过组合所有子结论来得出最终结论。如果有必要,一些无法比拟的结果会得到进一步处理。定义了直觉的语言-真实的估值函数,暗示了一种语言的直觉的模糊距离,证明了它是一个正的估值函数。无与伦比的结果排名方法利用语言直觉距离。最后,有关个人信用风险评估的示例说明了该方法的工作原理,而对比示例则表明该方法是合理的并且可以应用。

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