Abstract
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 Pythagoreanm-polar fuzzy weighted averaging (PmFWA), Pythagoreanm-polar fuzzy weighted geometric (PmFWG), symmetric Pythagoreanm-polar fuzzy weighted averaging (SPmFWA), and symmetric Pythagoreanm-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.
Highlights
Introduction and LiteratureReview e process of MCGDM focuses upon assisting the choice makers in evaluating the most appropriate choice amongst a finite number of options according to some criteria in such a manner that inclination of any member from the group towards a particular choice is diffused
Pythagorean m-polar fuzzy set is a mighty model for examining the information given in multipolar form
Pythagorean m-polar fuzzy weighted averaging operator, Pythagorean m-polar fuzzy weighted geometric operator, symmetric Pythagorean m-polar fuzzy weighted averaging operator, and symmetric Pythagorean m-polar fuzzy weighted geometric operator for the sake of aggregating the statistics given in multipolar form. e aggregated resultant falling in the same structure has been manifested
Summary
We recall some fundamentals of Pythagorean m-polar fuzzy sets and their operational laws accompanied by operational laws of corresponding numbers in this segment. Definition 1 (see [11]). A Pythagorean m-polar fuzzy set (PmFS) O (denoting aiffis lciahtaioranctdeergizreedes)byantdwoo (Ois)e(tsmoeafnmt afoprpidnigsssoΥci(Oai-). Tion grades) dropping members of X to [0, 1] constrained to obey 0 ≤ (Υ (Oi )( g ) )2 + ( o (O i) ( g ) ) 2 ≤ 1 , f or all i. E quantity ε(Oi)(g) 1 − (o (Oi)(g))2 − (Υ(Oi)(g)) is known as hesitation margin or indeterminacy degree of g ∈ X to O. Ε(Oi): X↦[0, 1] are mappings expressing lack of knowledge regarding g ∈ O or g ∉ O. acknowledged as Pythagorean fuzzy number (PFN)
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