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Relation between polling and Likert-scale approaches to eliciting membership degrees clarified by quantum computing

机译:轮询和李克特尺度方法之间的关系,以通过量子计算阐明隶属度

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In fuzzy logic, there are two main approaches to eliciting membership degrees: an approach based on polling experts, and a Likert-scale approach, in which we ask experts to indicate their degree of certainty on a scale - e.g., on a scale form 0 to 10. Both approaches are reasonable, but they often lead to different membership degrees. In this paper, we analyze the relation between these two approaches, and we show that this relation can be made much clearer if we use models from quantum computing.
机译:在模糊逻辑中,有两种主要的方法来得出隶属度:一种基于民意测验专家的方法,以及一种李克特量表方法,在这种方法中,我们要求专家在一个量表上(例如,以量表形式0)确定其确定性程度。到10。这两种方法都是合理的,但是它们通常会导致不同的成员资格程度。在本文中,我们分析了这两种方法之间的关系,并且表明,如果我们使用量子计算中的模型,则可以使这种关系更加清晰。

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