Batool Bushra, Ahmad Mumtaz, Abdullah Saleem, Ashraf Shahzaib, Chinram Ronnason
Department of Mathematics, University of Sargodha, Sargodha 40100, Pakistan.
Department of Mathematics, Abdul Wali Khan University, Mardan 23200, Pakistan.
Entropy (Basel). 2020 Mar 11;22(3):318. doi: 10.3390/e22030318.
The Pythagorean probabilistic hesitant fuzzy set (PyPHFS) is an effective, generalized and powerful tool for expressing fuzzy information. It can cover more complex and more hesitant fuzzy evaluation information. Therefore, based on the advantages of PyPHFSs, this paper presents a new extended fuzzy TOPSIS method for dealing with uncertainty in the form of PyPHFS in real life problems. The paper is divided into three main parts. Firstly, the novel Pythagorean probabilistic hesitant fuzzy entropy measure is established using generalized distance measure under PyPHFS information to find out the unknown weights information of the attributes. The second part consists of the algorithm sets of the TOPSIS technique under PyPHFS environment, where the weights of criteria are completely unknown. Finally, in order to verify the efficiency and superiority of the proposed method, this paper applies some practical examples of the selection of the most critical fog-haze influence factor and makes a detailed comparison with other existing methods.
毕达哥拉斯概率犹豫模糊集(PyPHFS)是一种表达模糊信息的有效、通用且强大的工具。它能够涵盖更复杂、更具犹豫性的模糊评价信息。因此,基于PyPHFS的优势,本文提出一种新的扩展模糊TOPSIS方法,用于处理现实生活问题中以PyPHFS形式存在的不确定性。本文分为三个主要部分。首先,利用PyPHFS信息下的广义距离测度建立了新颖的毕达哥拉斯概率犹豫模糊熵测度,以找出属性的未知权重信息。第二部分由PyPHFS环境下TOPSIS技术的算法集组成,其中准则的权重完全未知。最后,为了验证所提方法的有效性和优越性,本文应用了一些最关键雾霾影响因素选择的实际例子,并与其他现有方法进行了详细比较。