| Issue |
MATEC Web Conf.
Volume 189, 2018
2018 2nd International Conference on Material Engineering and Advanced Manufacturing Technology (MEAMT 2018)
|
|
|---|---|---|
| Article Number | 10008 | |
| Number of page(s) | 6 | |
| Section | Bio & Human Engineering | |
| DOI | https://doi.org/10.1051/matecconf/201818910008 | |
| Published online | 10 August 2018 | |
A learning-based system for predicting sport injuries
1
State Grid Corporation of China, Beijing, China
2
Shandong Luneng Sports & Culture Company, State Grid Shandong Company, Shandong, China
3
State Grid Shangdong Electric Power Company, Shandong, China
4
Shandong Luneng Software Technology Co., Ltd, Shandong, China
* Corresponding author: ls_sunht@163.com
In the big data era, learning-based techniques have attracted more and more attentions in many industry areas. The sport injury prediction is one of the most critical issues in data analysis of soccer teams.However, learning-based methods have not been widely used due to the poor data quality and computational capacity. In this paper, we propose a learning-based model to forecast sport injuries according to the data from various information systems. We first reduce the attributes that have significant impact on the injury risk by using learning-based methods.Then, we provide an algorithm based on the random forest method to prevent the over-fitting problem. We have evaluated the proposed model with the real-world data. The experimental results show that our model works efficiently and achieves low error rates.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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