To cultivate more application-oriented talents needed in the market, this paper puts forward a series of innovative development strategies for the integration of industry and education for the government, schools, and enterprises. The indicators used to determine whether the integration of industry and education is good or bad are relatively complicated because it is a long-term and complex teaching mode. In this paper, we use hierarchical analysis to construct a reasonable and clear evaluation index framework and use the convolutional neural network algorithm to calculate the weight value of each index, to comprehensively reflect the impact of the mechanism of industry-teaching integration on students, schools, and enterprises. According to the results of the evaluation system, the weights of the indicator "school running form"and the indicator "employment rate of graduates"reach 0.71 and 0.43 respectively, which fully indicates that the mechanism of integration of industry and education promotes the transformation of several courses in the school, and also helps students to solve the problem of employment. Employment Problems. In addition, the global weight value of the indicator "training cost of new employees"is only 0.01, which greatly reduces the recruitment and training cost of enterprises through the integration of industry and education. Therefore, the convolutional neural network adopted in this paper can effectively calculate the weight value and judge that the innovative development strategy of industry-teaching integration is of great help to all three parties. © 2024 Lei Wang, published by Sciendo.
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