Abstract
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.
Highlights
Artificial neural network (ANN) is an algorithm developed by artificial intelligence imitation on the basis of biological neural system model
After the construction of the sports injury estimation model based on the mutation fuzzy neural network, this paper analyzes through experiments and takes the Bayesian model and Lagrange Model as the comparison model of sports injury estimation, so as to carry out the estimation analysis of accuracy and efficiency
When the sample size reaches 50, the evaluation accuracy of the two comparative models drops to about 60%. e results of the evaluation and analysis of the sports injury degree by the model of the mutation fuzzy neural network show that the model of the mutation fuzzy neural network keeps a high precision level in the whole process of increasing the sample size from 10 to 50, and the precision is more than 90%. e results show that the model constructed in this paper gives full play to the advantages of fuzzy system and neural network algorithm in accuracy level and has obvious improvement in accuracy
Summary
Artificial neural network (ANN) is an algorithm developed by artificial intelligence imitation on the basis of biological neural system model. Rules are mainly provided or designed by experts, which makes the acquisition of rules cost and difficult Based on their respective advantages and disadvantages, a mutation fuzzy neural network is formed by combining the two. E development of artificial intelligence and big data makes the application of algorithm model in this field possible. E establishment of the model provides a theoretical basis for the application of big data algorithm for sports injury prevention and mutation fuzzy neural network in the field of sports. With the continuous development of science and technology, the algorithm model formed by the combination of fuzzy system and neural network has been widely used in many fields. Based on the advantages of this algorithm, this paper proposes a sports injury estimation model applied to a variety of sports fields
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