Research on the Innovation of Talent Cultivation Mode of Colleges and Universities Based on Big Data Technology Driven by School-Enterprise Cooperation

Abstract

Colleges and universities, as an important base for talent cultivation, are faced with the challenge of cultivating graduates adapted to the future needs of society and the market. The research firstly constructs the talent portrait of colleges and universities, carries out data collection and processing, for the problem of slow convergence speed of artificial bee colony algorithm for single peak problem, combines the improved artificial bee colony algorithm and fuzzy C-mean clustering algorithm to get the fuzzy C-mean clustering algorithm based on the improved artificial bee colony, and verifies it on the dataset, which finds that fuzzy C-mean clustering algorithm based on the improved artificial bee colony has more accuracy compared to traditional FCM with higher accuracy and the accuracy improvement reaches 90%. Through the improved clustering algorithm for cluster analysis, the students are finally classified into three types of students: self-disciplined learner type, night owl internet type and lack of planning type, on the basis of which a personalized teaching model for students' ability cultivation is designed. Finally, the BP neural network talent cultivation quality evaluation model was constructed and empirically analyzed. The study shows that the teaching mode can effectively improve the quality of talent cultivation in colleges and universities, and promote the innovative development of talent cultivation mode in colleges and universities and deepen the implementation of school-enterprise cooperation.