Study On Credit Evaluation Of Construction Enterprises Based On Rough Set And Two-tuple Linguistic

With the development of society,the construction of social credit system has been paid more and more attention by the whole society.In 2014,the State Council issued the “Outline of the Construction of Social Credit System”(2014-2020),which clearly pointed out that China will be committed to structure the credit of engineering construction field and credit of Bidding field.In the current construction market,due to the late start of credit management,the credit system is not perfect,construction enterprise credit management is particularly prominent.Construction enterprises as the main body of the construction market,some enterprises in the construction market activities in the existence of dishonesty,seriously affecting the construction market sustained and healthy development.Therefore,it is imperative to evaluate the credit of construction enterprises.Based on the characteristics of construction enterprises,this paper analyzes the characteristics and connotation of the construction enterprise credit,as well as the main reasons for the lack of credit.On the basis of following the basic principles of building enterprise credit index,through the investigation and reference state issued relevant documents of credit evaluation,establish the evaluation system of credit.After questionnaire survey and optimize by attribute reduction algorithm of rough set,construct a set of credit evaluation system of specialized construction enterprise and use AHP to determine the weight of indexes,selecting the model of based on two-tuple linguistic and grey clustering to evaluate the credit of construction enterprise.Finally,combined with the actual case,the index system and evaluation model are tested,verify the scientific and practical of index system and evaluation model.