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With the rapid development of society and the rise of the knowledge economy, cultivating the innovation and entrepreneurship abilities of college students has gradually become an important task of higher education. However, in the current educational environment, the cultivation of innovation and entrepreneurship abilities among college students faces a series of issues, such as the disconnect between knowledge and practice, and the singularity of training methods. To address these issues, an analysis of existing innovation and entrepreneurship education was conducted using project management method. A combination model for cultivating innovation and entrepreneurship abilities among college students was constructed using Analytic Hierarchy Process (AHP) and entropy method. Considering that the talent cultivation combination model belongs to a complex nonlinear solving problem, an advanced ABC-BP combination model was adopted to handle the linear data problem of the model. Among them, the Back Propagation (BP) model was used to train and refine the linear parameters of the cultivation model, and to explore the optimal combination factors. Considering that the BP model is prone to local convergence and parameterization problems, the Artificial Bee Colony (ABC) algorithm optimized the parameters of the model, improved the training effect of the model, and enhanced the application effect of the combination model for cultivating innovation and entrepreneurship abilities. In the training test of the model, compared with the classic BP model and Particle Swarm Optimization (PSO) model, the proposed ABC-BP model had lower overall RMSE, greater optimization precision and faster convergence speed in terms of optimization results. Compared with the BP model and the PSO model, the training precision of the ABC-BP model has increased by 14%. The ABC-BP model was selected to solve the talent training combination model. According to the solution results, the highest comprehensive score of scheme 1 was 0.57, and scheme 1 was finally selected as the best scheme for talent training. This study has important reference significance for the cultivation of innovative and entrepreneurial talents in China. Through AHP and optimization methods, the effectiveness of cultivating innovation and entrepreneurship abilities among college students can be improved, and more talents with innovation and entrepreneurship abilities can be cultivated to meet the needs of rapidly developing society and knowledge economy.
Wei et al. (Thu,) studied this question.