In order to solve the current problem of low willingness of college students to innovate and start a business, this paper puts forward the method of college students’ innovation and entrepreneurship incentive mechanism based on analytic hierarchy process, improves the innovation and entrepreneurship incentive system for college students, optimizes the evaluation index of innovation and entrepreneurship of college students through the analytic hierarchy process, combines the triangular fuzzy number to express the weight evaluation value of the enterprise environmental behavior index, uses the binary semantics to express the evaluation value of the evaluation subcriteria to the enterprise environmental behavior, optimizes the evaluation algorithm, and selects a reasonable college students’ innovation and entrepreneurship incentive scheme. The experimental verification results show that the data of innovation and entrepreneurship activities of the proposed method based on analytic hierarchy process for the construction of incentive mechanism for innovation and entrepreneurship of college students are more than 70%, and the highest is 84.5%. The rationality of the method is more than 90%, and the highest is 96.1%. It has high practicability in practical application process and can better encourage college students to participate in innovation and entrepreneurship activities.

With the economic development in recent years, the state has paid more and more attention to education, and more and more college graduates have been graduated. The purpose of this paper is to study how to analyze the refinement method of evaluating the innovation and entrepreneurship ability (IEA) of colleges and universities based on the optimal weight model. This paper proposes a sorting refinement method based on the optimal weight model and uses the BP neural network to determine the optimal weight. Weight is a scoring mechanism for comprehensive ranking, that is, a scoring system. The higher the score, the higher the weight, and the higher the ranking of the relative things. The experimental results of this paper show that in 2013, the number of college graduates in China reached 6.09 million, but the number of employed people was only 4.67 million, an increase of 120,000 over the same period. By 2020, the number of college graduates in China has reached 7.27 million, and the number of employed people has been 5.78 million. However, the number of employed persons is always lower than the number of graduates, indicating that employment is difficult. Under this situation, many college graduates choose to start their own businesses, but the success rate of entrepreneurship is also very low, only about 3%. This shows that the IEA of college graduates is not high, so it is necessary to improve the IEA and conduct self-evaluation.