Yogananda School of AI, Computer and Data Sciences, Faculty of Engineering and Technology, Shoolini University, Solan 173229, Himachal Pradesh, India.
Research Team on Intelligent Decision Support Systems, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland.
Sensors (Basel). 2022 Jun 28;22(13):4879. doi: 10.3390/s22134879.
The Pythagorean fuzzy sets conveniently capture unreliable, ambiguous, and uncertain information, especially in problems involving multiple and opposing criteria. Pythagorean fuzzy sets are one of the popular generalizations of the intuitionistic fuzzy sets. They are instrumental in expressing and managing hesitant under uncertain environments, so they have been involved extensively in a diversity of scientific fields. This paper proposes a new Pythagorean entropy for Multi-Criteria Decision-Analysis (MCDA) problems. The entropy measures the fuzziness of two fuzzy sets and has an influential position in fuzzy functions. The more comprehensive the entropy, the more inadequate the ambiguity, so the decision-making established on entropy is beneficial. The COmplex PRoportional ASsessment (COPRAS) method is used to tackle uncertainty issues in MCDA and considers the singularity of one alternative over the rest of them. This can be enforced to maximize and minimize relevant criteria in an assessment where multiple opposing criteria are considered. Using the Pythagorean sets, we represent a decisional problem solution by using the COPRAS approach and the new Entropy measure.
毕达哥拉斯模糊集方便地捕获不可靠、模糊和不确定的信息，特别是在涉及多个和对立标准的问题中。毕达哥拉斯模糊集是直觉模糊集的一种流行推广。它们在表达和管理不确定环境下的犹豫方面非常有用，因此已经广泛应用于各种科学领域。本文提出了一种新的用于多准则决策分析（MCDA）问题的毕达哥拉斯熵。熵度量两个模糊集的模糊度，在模糊函数中具有重要地位。熵越全面，模糊度越低，因此基于熵的决策是有益的。COmplex PRoportional ASsessment（COPRAS）方法用于解决 MCDA 中的不确定性问题，并考虑一个替代方案相对于其他方案的奇异点。这可以通过最大化和最小化评估中考虑的多个对立标准来实现。我们使用毕达哥拉斯集通过 COPRAS 方法和新的熵度量来表示决策问题的解决方案。
