Application of the intelligent back propagation neural network in the optimization of sports industry structure - Xianhe Zhou; Yan Zhu (Scientific Reports)
Abstract To explore the application potential of the intelligent Back Propagation Neural Network (BPNN) in the optimization of sports industry structure, a new intelligent BPNN model is constructed in this study. Firstly, the development status of the sports industry is introduced. Secondly, the principle and structure of intelligent BPNN are analyzed in detail. Finally, the BPNN model’s architecture is optimized, and experiments verify the optimized model’s effectiveness. The experimental dataset selected is the Kaggle-Sports Category dataset. The experimental results show that the proposed optimized model achieves a high score of 0.90 in user satisfaction. Meanwhile, it significantly outperforms the compared model in economic benefits, with a gain rate of 0.95 in box office revenue. In addition, although the proposed optimized model has slightly higher operating costs than other models, its excellent performance in resource utilization and economic benefits is sufficient to fill this gap. These experimental results prove the optimized model’s application value in optimizing sports industry structure. This study provides valuable references for using intelligent technology, especially intelligent BPNN, to maximize the sports industry structure.