Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis

Abstract

The sports economy also occupies a main part of the national economy, which requires professionals to be able to evaluate the development of the sports economy. The sports industry will generate cumbersome data, which are important for the future development trend of the sports economy. This research will collect a large amount of data from the sports industry, data mining technology, and neural network method that will be used to fully mine and predict the relationship between sports economic data, and it will provide corresponding management references for sports industry companies. Some important statistical parameters will be used to evaluate the feasibility of data mining techniques and neural network methods in sports economic management. The research results show that the error of data mining technology in the classification of sports economy is within 2.54%, and the prediction error of the neural network method is also within 3.2%. This shows that the data mining technology proposed in this study is feasible for classification and prediction application in sports economic management. Once the forecast data of the sports economy are output through the output layer, the sports economy managers can rely on these data to manage and adjust the relevant factors of the sports economy.