模糊语言变量和模糊表达式的定性和量化

Yingxu Wang
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引用次数: 2

摘要

模糊逻辑的本质之一是如何在模糊推理中将模糊变量和模糊表达式转化为精确的量和严格的模型。本文提出了认知信息学、软计算和计算智能中模糊资格和量化建模的指称数学结构和方法。在离散和连续模糊对象和表达式上,对绝对度量和相对度量的模糊定性和量化进行了形式化阐述。此外,对模糊对象的特征属性进行了定性建模。模糊定性和量化的应用是用一组丰富的例子和现实世界的案例来说明的,这使得机器能够模仿认知信息学、软计算和计算智能中复杂的人类推理机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Qualification and quantification of fuzzy linguistic variables and fuzzy expressions
One of the essences of fuzzy logic is how fuzzy variables and fuzzy expressions may be transformed into precise quantities and rigorous models in fuzzy inferences. This paper presents a denotational mathematical structure and methodology for modeling fuzzy qualifications and quantifications in cognitive informatics, soft computing, and computational intelligence. Fuzzy qualifications and quantifications for both absolute and relative measures are formally elaborated on discrete and continuous fuzzy object and expressions. In addition, the qualification for characteristic attributes of fuzzy objects is modeled. Applications of fuzzy qualifications and quantifications are illustrated using a rich set of examples and real-world cases, which enable machines to mimic complex human reasoning mechanisms in cognitive informatics, soft computing, and computational intelligence.
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