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Model‐based evaluation for online shopping platform with probabilistic double hierarchy linguistic CODAS method
Author(s) -
Lei Fan,
Wei Guiwu,
Chen Xudong
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22514
Subject(s) - hierarchy , probabilistic logic , computer science , the internet , artificial intelligence , analytic hierarchy process , natural language processing , world wide web , mathematics , operations research , economics , market economy
With the rapid advancement of Internet technology, the number of online shopping platforms has been increasing. Poor online shopping platform causes all sorts of trouble among the people despite convenience. A comprehensive and reasonable evaluation of online shopping platforms is of great significance. Therefore, this study establishes an online shopping platform evaluation model based on probability double linguistic‐combinative distance‐based assessment (PDHL‐CODAS). First, the notion of probabilistic double hierarchy linguistic term sets (PDHLTSs) is reviewed. Then the distance formulas of PDHLTS are defined. Thereafter, cumulative prospect theory is used to generate the cumulative weight of probabilistic double hierarchy linguistic information. Additionally, the integrated determination of objective criteria weights method is introduced to calculate the objective weight. PDHL‐CODAS method is established and applied to the evaluation of online shopping platforms. Finally, unlike the available probabilistic double hierarchy linguistic multiple attribute decision making methods, the defined method is scientifically effective.