Abstract
With the continuous development of track and field sports, a relatively complete and scientific system has been formed in terms of training, and more attention has been paid to the planned training of teenagers for many years, psychological training and recovery training, and strengthening medical supervision and scientific research. In order to speed up the scientific training of track and field and improve the level of track and field training in China, in view of the characteristics of track and field injuries such as multiple causes and complexity, this paper analyzes and studies the attribute reduction algorithm based on attribute reduction algorithm, and proposes a sports injury early warning model based on mutual information. Taking the reduction results as input neurons, a BP neural network with hidden layer is established in MATLAB environment. The results show that: call 85% of the track and field athletes in the sample information as training samples for training. After the simulation experiment of the model, it is found that the error value of the prediction results is basically controlled in the range of-0.025-0.05, which meets the requirements of early warning accuracy of injury risk level of athletes, and the accuracy rate of early warning of sports injury risk reaches 100%.
Highlights
Track and field is one of the important sports events
With the continuous development of track and field sports, a relatively complete and scientific system has been formed in terms of training, and more attention has been paid to the planned training of teenagers for many years, psychological training and recovery training, and strengthening medical supervision and scientific research [1, 2].The improvement of field equipment, and many scientific research results directly or indirectly applied to track and field sports practice, doping detection means reached a very high level, all of which promote and ensure the healthy and rapid development of track and field and the improvement of sports performance
In order to speed up the scientific track and field training and improve the level of track and field training in our country, aiming at the characteristics of track and field injuries such as multiple causes and complexity, this paper analyzes and studies the attribute reduction algorithm based on attribute importance, and proposes a reasonable and effective attribute reduction algorithm based on attribute importance, which is applied to the early warning model of track and field injury risk
Summary
Track and field is one of the important sports events. It includes race walking, middle and long distance running, jumping, throwing and all-round sports, with more than 40 single events. In June 2012, Liu Xiangping, a flying man in the Youjin station of the Diamond League, won the world record and won the championship He withdrew from the Olympic Games due to injury before the final in London in midJuly. At the London Olympic Games in August 2012, Liu Xiang left the Olympic Games with doubts and praises because of his Achilles tendon injury [4, 5].it is of direct and important significance to investigate and analyze the injuries and injuries of professional athletes in track and field, summarize their injuries, similarities in similar events, injury prone time periods and parts, and reduce the incidence of sports injuries, which is of direct and important significance for ensuring athletes' sports skills and career. The identification of athletes at high risk of MUSINJ is done for screening program validation for MUSINJ prevention program establishment [10].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
