Evaluation and Prediction of Sports Health Literacy of College Students Based on Artificial Neural Network

Abstract

Sports health literacy (SHL) is an important indicator of the all-round development of college students. However, the existing studies have not constructed a systematic and complete evaluation index system (EIS) or diversified the index weighting method. To solve the problem, this paper tries to evaluate and predict college students’ SHL based on artificial neural network (ANN). Firstly, an EIS was designed for college students’ SHL, including 4 goals, and 19 primary indices, and the structure of the evaluation and prediction system was presented for college students’ SHL. Next, college students’ SHL was comprehensively evaluated through analytic hierarchy process (AHP). Finally, a backpropagation neural network (BPNN) was established to predict college students’ SHL, and the initial weights were optimized by genetic algorithm (GA). The proposed EIS and prediction model were found scientific and effective through experiments. To sum up, the SHL of college students were evaluated and predicted in the following aspects: EIS construction, evaluation model establishment, and evaluation system design. The proposed model and system can comprehensively rate college students’ SHL. The statistical analysis of the ratings reflects the gaps between indices, and identifies those doing well and poorly on each index. Then, pertinent intervention can be implemented to satisfy the actual needs of improving college students’ SHL.