A Basketball Technique Balance Control Technology Based on Ant Colony Algorithm
Author(s) -
Yong Wang,
Yongxin Du
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/6559098
Subject(s) - basketball , computer science , ant colony optimization algorithms , algorithm , balance (ability) , stability (learning theory) , control (management) , artificial intelligence , simulation , machine learning , physical medicine and rehabilitation , medicine , archaeology , history
Aiming at the problems of low accuracy, poor stability, and effect of balance control in the current basketball skill balance control process, a basketball skill balance control method based on ant colony algorithm is proposed. The principle and characteristics of ant colony algorithm are analyzed, the mathematical model of ant colony algorithm is established, and the implementation steps of ant colony algorithm are given. According to the balance and stability control principle of basketball skills, this paper constructs the balance and stability control model of basketball skills. By establishing the knee-ankle-foot joint analysis model and using the ant colony algorithm, the basketball movement path is constructed. Through the fitness function, select the basketball motion path nodes and update the pheromone, obtain the relationship between the internal stress and displacement of the body under different force directions, and obtain the influence law of the effective knee joint stress with the varus and internal rotation, so as to achieve the balance and stability of the basketball skills sexual control analysis. The experimental results show that the proposed method has better stability and effect of basketball technique balance control and can effectively improve the accuracy of basketball technique balance control.
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