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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
An integrated ELECTRE method for selection of rehabilitation center with m-polar fuzzy N-soft information
Muhammad Akram1, Maheen Sultan1, José Carlos R Alcantud2
1Department of Mathematics, University of the Punjab, New Campus, Lahore, P.O. Box 54590, Pakistan.
Abstract:
The primary goal of this research article is to apply ELECTRE I, a fundamental multi-criteria group decision-making technique, in an m-polar fuzzy N-soft environment. This new methodology helps us to pinpoint the best alternative(s) in the presence of multi-polar options with N-graded qualities. Its basic operational idea entails the comparison between any two alternatives by the assessment of score degrees. Concordance and discordance indices are then calculated to evaluate the alternatives' superiority and inferiority. We may disqualify the incompetent alternatives using concordance and discordance levels. An m-polar fuzzy N-soft dominance matrix can represent the combined effect of concordance and discordance dominance matrices. The steps of this new multi-criteria group decision making technique are summarized in a flowchart. In order to demonstrate its authenticity and applicability, we employ a case study involving the establishment of a rehabilitation facility for drug abusers. A comparison with the m-polar fuzzy PROMETHEE and m-polar fuzzy ELECTRE I methodologies establishes its validity. Finally, we conclude our study of the methodology proposed in this paper with a critical analysis of its benefits and drawbacks.
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