A novel linguistic decision making approach based on attribute correlation and EDAS method

Abstract One of characteristics large-scale linguistic decision making problems is that information with respect to attributes derived from multi-sources information. In addition, the number makers, alternatives or criteria in context big data are increasingly large. Correlation analysis between has become an important issue problems. paper, we concentrate on correlation deal intuitionistic fuzzy values. Firstly, proposed a new similarity measure two sets formally define attributes. Then propose reducible weighted Maclaurin symmetric mean (LIFRWMSM) operator and dual (LIFRWDMSM) aggregate value correlational attributes, analyze several properties operator. Inspired by evaluation based distance average solution (EDAS) method, design scheme steps To show effectiveness usefulness employ choice buying house selection travel destination demonstrate our method make comparative others aggregation operators methods.