Sports Energy Consumption Estimation Model Based on Intelligent Algorithm and Big Data

With the continuous development of science and technology, the application of intelligent algorithms and big data in sports science is becoming more and more extensive. This article aims to discuss the principles, methods and applications of the sports energy consumption estimation model based on intelligent algorithms and big data. This paper adopts the method of combining survey experiment and empirical research to discuss the estimation model of sports energy consumption based on intelligent algorithm and big data. Firstly, this paper introduces the existing sports energy consumption estimation models, and analyzes their advantages and disadvantages. Then, this paper elaborates the design and implementation process of the sports energy consumption estimation model based on intelligent algorithms and big data, including the model's architecture, algorithms and data sources. Finally, the paper summarizes the strengths and limitations of the model and points out corresponding measures. The experimental results show that the error rate of the intelligent algorithm estimation model for the energy consumption of fast walking sports is 10.1%, and the accuracy is relatively high.