Simulation of Sports Monitoring System Based on Feature Network

Abstract

In recent years, the network can gradually express more and more complex systems. In the process of network expression, the basic elements of the system are defined as nodes, and the interaction relationship is defined as links. In the current application process, network data are diversified, some express feature structure information, and some express node attribute data. In practice, there is a lot of feature information of network nodes, many of which are redundant. How to filter out the redundant and useless feature information has become an important problem. So that, the feature network is applied, and the node feature correction method is designed. The weight method is used to express the relative importance of the feature problem. At present, the main discovery algorithms can only find the network structure features, and the clustering algorithm can only find the feature information about the network nodes. Therefore, this paper builds an embedded platform based on the remote control and constructs an embedded motion monitoring system. This paper starts with experimental research and completes the design of nutrition scheme through big data analysis method to enhance students' physique. In this paper, we use the feature network to complete the embedded sports monitoring system and put forward several suggestions to improve sports nutrition management.