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Analysis of Sports Injury Estimation Model Based on Mutation Fuzzy Neural Network. 2021

Dong Wang, and Jeng-Sheng Yang
College of Sports Rehabilitation, Shanxi Medical University, Taiyuan, Shanxi 030001, China.

In recent years, with the gradual development of sports, the competition between athletes is becoming more and more fierce. The long training time and heavy body load of athletes lead to the increase of the incidence of sports injury, and the evaluation and analysis of athletes' sports injury need a lot of manpower and material resources. In order to improve the calculation efficiency of sports injury estimation results and save the cost of estimation and analysis, we propose a sports injury estimation model based on the algorithm model of mutation fuzzy neural network. The sports injury model constructed in this paper can not only systematically evaluate and analyze the degree of sports injury of athletes, but also improve the accuracy and efficiency; at the same time, it has universality for the evaluation and analysis of the degree of sports injury. The construction of this model provides the theoretical basis of big data algorithm for the prevention of sports injury and the application of mutation fuzzy neural network in the field of sports.

UI MeSH Term Description Entries
D009154 Mutation Any detectable and heritable change in the genetic material that causes a change in the GENOTYPE and which is transmitted to daughter cells and to succeeding generations. Mutations
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001265 Athletic Injuries Injuries incurred during participation in competitive or non-competitive sports. Sports Injuries,Injuries, Athletic,Injuries, Sports,Athletic Injury,Injury, Athletic,Injury, Sports,Sports Injury
D013177 Sports Activities or games, usually involving physical effort or skill. Reasons for engagement in sports include pleasure, competition, and/or financial reward. Athletics,Athletic,Sport
D016571 Neural Networks, Computer A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D056352 Athletes Individuals who have developed skills, physical stamina and strength or participants in SPORTS or other physical activities. College Athletes,Elite Athletes,Professional Athletes,Athlete,Athlete, College,Athlete, Elite,Athlete, Professional,Athletes, College,Athletes, Elite,Athletes, Professional,College Athlete,Elite Athlete,Professional Athlete

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