Research On Method For Sequencing Linguistic Decision Based On Set Pair Analysis

In general, the customer has a certain complexity, and the human mind has acertain ambiguity, in the process of multiple attribute decision making, decisionmakers often use sequencing language phrase qualitative evaluation on theproperties of things. A buildup of effective linguistic assessment information,which ensures the accuracy and effectiveness of the decision results, and thisinformation has gradually aroused the people’s attention.Due to the different decision makers has different opinions for the sameword meanings, or the same decision makers has different understanding indifferent cases of the same words, the result is not often in conformity with agiven set of linguistic assessment through extending the principle and based onthe symbolic transfer method, in this case, language approximate evaluation setcan only be identified, which will cause the deviation of language informationand loss. Usually, according to the known data, data attribute analysis is donebefore people making a statistical decision, and the survey data are classified,before the attribute analysis.In this article, the information of the uncertain part stating incorrect and theproblem of information lost have been researched, in view of the data which needto be classified of ordinal scale is transferred into quantitative data. In this paper,Sequence of language information granularity is deal with flexibility by the setpair analysis method, and the problem of scale division of coarse languageinformation is resolved, and the sequencing language information scale resultsinaccurate is avoided, and the problem of unable to distinguish between solutioneffectively is solved, and the language scale is improved, and the languagemeaning is more in line with the decision makers’ expectations. The concept ofD-U space is introduced in the process of language information aggregation, andthe decision method is raised, during this process, the uncertainty of languageinformation is considered, and the problem of type mismatch of language information description is solved, and the problem of mismatch of choosingexperts in linguistic term set granularity is solved, and then, the accuracy ofdecision-making is improved. Through the empirical study, the effective andpractical of the method is verified.