Track Cycling Training Analysis System Design Based On Fuzzy Neural Network

With the rapid development of our economy, cycling is also developing rapidly. But, the overall level of our country’s cycling still have a certain gap with world powers. In order to help athletes achieve better results, not only requires the athletes to improve their physical fitness, the scientific training equipment and training methods are all important. The research content of this article is cycling training analysis system based on the fuzzy neural network. It can real-time display the athletes’training data, and statistical analysis on the athletes’ training data. To help coaches real-time grasp the training data of athletes, raise the level of the athletes’ training.In this topic, write intelligent detection analyzer of track cycling training analysis system through the software Lab VIEW developed by NI. In order to real-time monitoring the training process of cyclists, record the training data and statistical analysis, to help athletes improve training efficiency, real-time measurement and display the athlete’s heart rate and cycling speed; Measure the athletes reaction time, the designated time-consuming data through runway and calculated the actual ride away; Store the data in the database, the training data can be read at any time and make the comparison analysis of athletes.Use the Adaptive Fuzzy-Neural Inference system (ANFIS) to statistical analysis the parameters of athletes,help coaches to have more detailed and comprehensive grasp of athletes training effect. This paper first researched the artificial neural network control and the typical RBF neural network and hybrid learning algorithm. Expounds the basic theory and research achievements of fuzzy control, and introduced ANFIS structure, learning algorithm and the modeling process. Finally, using virtual instrument technology combined with ANFIS established monitoring and evaluation system of cycling.