Evaluation Method of Rationality of Creative Genius Cultivation Pattern Based on a BP Neural Network. (20th September 2022)

• Record Type: Journal Article
• Authors: Li, Yong; Dong, Kailing; Wang, Qingyuan
• Other Names: Fan Yaxiang Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2022(2022)
• Publication Date: 2022-09-20
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2022/4639308
• Languages: English
• ISSNs: 1687-5265

Abstract

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.