Abstract
Aiming at solving the problem of poor performance of airborne freestyle skiing balance, this paper presents the research of airborne freestyle skiing balance control based on ant colony algorithm. On the basis of defining the trajectory division of the airborne balance of freestyle skiing and the track of the center of gravity of the human body, a sensor is used to collect the data of the airborne balance of freestyle skiing, and the moving average, denoising, and normalizing processes are done. The training label of the ant colony algorithm is made by the analog signal matrix, the implementation foreground of the key posture frame of freestyle skiing is extracted, the disturbed area in the key posture frame is removed by the clustering algorithm, and the key posture area of freestyle skiing is obtained. The incremental clustering of the data of the key posture area of freestyle skiing is conducted, the incremental posture data mining model of freestyle skiing is established, the mining parameters are input into the mining model, and the incremental data mining is realized by the ant colony algorithm to complete the research on the control of the airborne balance of freestyle skiing. The results show that the proposed method has good reliability, good convergence, and strong response ability.
Highlights
Security and Communication NetworksStudies have shown that the mechanism of balance control involves sensory input, central integration, and motor control. e stability and directionality require complex interactions between the musculoskeletal system and the nervous system
E research contributions of this article include the following: (1) Aiming at solving the problem of poor performance of airborne freestyle skiing balance, this paper presents the research of airborne freestyle skiing balance control based on ant colony algorithm
E total number of airborne balance control packets for different methods of freestyle skiing over a 100 ms period is shown in Table 2. e method in this paper can control 175468.6 kb data per 10 ms on average, while the methods of references [3] and [4] can only control 119955.7 kb and 119955.773.2 kb, respectively. e method in this paper is obviously superior to the methods of references [3] and [4], with 55512.9 kb and 37895.4 kb, respectively. erefore, this paper designs a balance control method of freestyle skiing airborne skill based on ant colony algorithm, which can control more data in unit time and has better performance
Summary
Studies have shown that the mechanism of balance control involves sensory input, central integration, and motor control. e stability and directionality require complex interactions between the musculoskeletal system and the nervous system. Erefore, a research on the balance control of airborne freestyle skiing skills based on ant colony algorithm is proposed. (1) Aiming at solving the problem of poor performance of airborne freestyle skiing balance, this paper presents the research of airborne freestyle skiing balance control based on ant colony algorithm (2) On the basis of defining the trajectory division of the airborne balance of freestyle skiing and the track of the center of gravity of the human body, a sensor is used to collect the data of the airborne balance of freestyle skiing, and the moving average, denoising, and normalizing processes are done. Snowboard slide track Traject of body center of gravity A, B Intersection of two trajectories
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