A Research Of 3000 Meters Steeplechase Performance Forecast Model Based On The BP Neural Network And Physiological Index

With the development of economic, the demand of human material life and spiritual life has been increased a lot and port has become an indispensable part of our daily life. Although 3000 meters steeplechase was proposed a little late, it was loved by the people all over the world and increasingly attracts more and more attention in the field of world competitive sports. From the theoretical study of the 3000 meters steeplechase project, we can see that the researches of the project are more concentrated on the project training, material choosing and how to improve the technology of crossing barriers or over the pool, and the research of 3000 meters steeplechase results are limited to the development trend analysis, the study of results prediction cannot be found, which restricts the development of this project to some extent, and become a good point cut for us to study the 3000 meters steeplechase project. Artificial neural network is a new kind of intelligent information processing theory which developed in the process of imitating brain to solve problems. BP neural network is one of the most widely used neural network model that can be used as classification, clustering, forecasting and other related issues. In this paper, we normalized all index, took them as the input, and the results of 3000 meters steeplechase as the output of the network, then we use the trained model to predict the results, in this way,we can get a accurately predicting results for athletes. This study, to some extent, provides a theoretical basis for the adjustment of 3000 meters steeplechase athletes and improves their athletic performance.