ABSTRACT

In the application phase of the fuzzy theory, it is an obvious advantage to have a valuable defuzzification. The defuzzification method that we deal with in this work is a flexible, adaptable and multi-purpose method. In this study, we will introduce a new concept to obtain the parameter values of the defuzzification method called WABL. The new concept is based on maximizing the entropy of the level sets weights of the method. We develop two versions for the concept. In the first one, we suppose that we have one decision-maker to supervise a fuzzy process. In the second version, we assume that we have a group of decision-makers to collectively administrate a fuzzy process. For each version, we construct a constrained optimization problem and we solve each problem analytically. The working results of the versions are demonstrated by numerical examples.

摘要

在模糊理论的应用阶段，进行有价值的去模糊化具有明显的优势。我们在这项工作中处理的去模糊方法是一种灵活，适应性强且用途广泛的方法。在这项研究中，我们将介绍一个新概念来获取称为WABL的反模糊化方法的参数值。新概念基于最大化该方法的级别集权重的熵。我们为该概念开发了两个版本。在第一个例子中，我们假设我们有一个决策者来监督模糊过程。在第二个版本中，我们假设我们有一组决策者来集体管理模糊过程。对于每个版本，我们都会构造一个约束优化问题，然后通过分析来解决每个问题。