Pythagorean m-Polar Fuzzy Weighted Aggregation Operators and Algorithm for the Investment Strategic Decision Making

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 wi...

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Bibliographic Details
Published inJournal of mathematics (Hidawi) Vol. 2021; pp. 1 - 19
Main Authors Riaz, Muhammad, Naeem, Khalid, Chinram, Ronnason, Iampan, Aiyared
Format Journal Article
LanguageEnglish
Published Cairo Hindawi 2021
Hindawi Limited
Subjects
Agglomeration
Algorithms
Decision making
Fuzzy sets
Mathematics
Operators (mathematics)
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Summary: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.
ISSN:2314-4629
2314-4785
DOI:10.1155/2021/6644994