Application of Optimized Fuzzy Decision Tree Algorithm in Sports Video Analysis

Abstract

In sports video prediction, a very important link is the model. The traditional fuzzy algorithm based on classical fuzzy algorithm can no longer meet the needs of the development of the times. So this paper improves and optimizes this problem and gets a more accurate, practical, fast and intuitive result. The objective function-weight vector method replaces the artificial neural network to train the decision tree algorithm, and applies it to the establishment of sports video evaluation index system based on motion control quantity. Finally, the feasibility and effectiveness of the model in practical application are verified by experiments. The verification results show that, The running time of fuzzy decision tree algorithm is within 11-17 seconds, and the running efficiency is more than 80%. This shows that the algorithm has obvious optimization effect on sports video analysis.