Research on Intelligent Access Optimization Model of Power Construction Subcontractors Based on Data Mining Algorithm

The selection of subcontractors for power enterprises is a critical step in the successful completion of construction tasks. Improper selection of subcontractors will bring various risks to the construction. This paper innovatively proposes the selection of subcontractors based on set pair analysis and entropy weight principle. This method overcomes the shortcomings of traditional evaluation methods that are easily affected by experts' preferences or experience to a certain extent. This paper firstly determines the evaluation index system of construction subcontractors of construction enterprises. Based on the concepts of joint fuzzy set and joint membership degree, this paper establishes and identifies the evaluation mode of construction subcontractors in construction enterprises by applying fuzzy set closeness degree. In the end, this paper determines the ideal subcontractor by two-stage evaluation method.