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Pythagorean m-Polar Fuzzy Weighted Aggregation Operators and Algorithm for the Investment Strategic Decision Making
oleh: Muhammad Riaz, Khalid Naeem, Ronnason Chinram, Aiyared Iampan
Format: | Article |
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Diterbitkan: | Wiley 2021-01-01 |
Deskripsi
The role of multipolar uncertain statistics cannot be unheeded while confronting daily life problems on well-founded basis. Fusion (aggregation) of a number of input values in multipolar form into a sole multipolar output value is an essential tool not merely of physics or mathematics but also of widely held problems of economics, commerce and trade, engineering, social sciences, decision-making problems, life sciences, and many more. The problem of aggregation is very wide-ranging and fascinating, in general. We use, in this article, Pythagorean fuzzy numbers (PFNs) in multipolar form to contrive imprecise information. We introduce Pythagorean m-polar fuzzy weighted averaging (PmFWA), Pythagorean m-polar fuzzy weighted geometric (PmFWG), symmetric Pythagorean m-polar fuzzy weighted averaging (SPmFWA), and symmetric Pythagorean m-polar fuzzy weighted geometric (SPmFWG) operators for aggregating uncertain data. Finally, we present a practical example to illustrate the application of the proposed operators and to demonstrate its practicality and effectiveness towards investment strategic decision making.