Sports Risk Prediction Model Based on Automatic Encoder and Convolutional Neural Network

In view of the limitations traditional statistical methods in dealing with multifactor and nonlinear data inadequacy classical machine learning algorithms predicting high dimensions large sample sizes, this paper proposes an operational risk prediction model based on automatic encoder convolutional neural networks. First, we use to extract features motion factors obtain feature components that can highly represent risk. Secondly, causal relationship between sports characteristics, a network dual convolution layer pooling topology is constructed. Finally, established by combining auto-coded network. Compared other algorithms, proposed method effectively analyze characteristics has accuracy. At same time, it promotes integration science computer provides basis for application field prediction.