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Evaluation Method of Rationality of Creative Genius Cultivation Pattern Based on a BP Neural Network
Yong Li1, Kailing Dong2, Qingyuan Wang1
1Chengdu University, Chengdu, Sichuan 610106, China.
Abstract:
In order to realize the evaluation of the rationality of an innovative talent training mode, an evaluation model of the rationality of the innovative talent training mode based on a BP neural network is proposed. On the basis of clarifying the principle of the BP neural network model, according to the method of parameter multisource control analysis, the multi-objective characteristic analysis of the rationality of the innovative talent training mode is realized to measure the difference and balance between the two variables of the rationality of the innovative talent training mode. A BP neural network algorithm is designed to find the best feature subset, and a feature sequence sampling and recombination model is constructed. Through reliability evaluation and nonparametric quantitative feature estimation, quantitative analysis and evaluation of the rationality of the innovative talent training mode are realized. The test results show that the confidence level and reliability of the rationality evaluation of the innovative talent training mode using this method are high.
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