[Retracted] Intelligent Design of Tennis Player Training Schedule Based on Big Data of Complexity

Abstract

Tennis players have more physical training content, and the training items are complex. For athletes, training programs that adapt to their individual characteristics should be formulated according to their physical characteristics. The current development of big data has brought about changes in thinking, management, and business models. The combination of complex systems and big data can also make breakthroughs in the sports field. Based on this, this article proposes a tennis player training schedule intelligent formulation system based on complex system big data. First of all, this article adopts the literature data method, comparative analysis method, experimental analysis method, etc., in-depth study of the concepts of big data, complex system, and the physical structure characteristics of tennis sports. This paper designs an intelligent system for making tennis players’ training schedule, which collects, transforms, and integrates tennis training data through the characteristics of big data. Then, the dynamic time regulation of tennis is performed through a complex system, and finally, the experimental system is analyzed. This article mainly analyzes the comparison of physical indicators between the experimental group and the control group before and after the experiment, the evaluation indicators of sports events, the strength training effects of tennis events, and the analysis of shoulder joint tests. There is no significant difference between the experimental group and the control group in the items before the experiment, P > 0.05 , which suggests that the physical fitness of the two groups of athletes is similar; in the posttest data, the experimental group and the control group have significant differences, P < 0.05 , indicating an effect from the experiment. In particular, in fan running, forward and backward strokes, and the serve, the scores of the experimental group were higher than those of the control group, indicating that the use of the formulated training system demonstrated significant results.

Multitask Multi attention Residual Shrinkage Convolutional Neural Network Personalized Assessment Model of Tennis Teaching Based on Data Mining and Intelligent Recommendation

“…People's production, lives are changing the world. Running big data tasks on mobile platforms has become more common in current years, thanks to growing mobile devices, increasing computing power of mobile processors [1].Running big data applications on mobile platforms enables inventers to rapidly utilize novel big data processes to mobile platforms, allowing people to access big data services at any time, from any location, refining productivity, quality of life, stimulating industrial renovation [2][3][4].Chinese tennis began late on international stage, so relative level is lower, development rate is slow; primary causes for this tennis's lack of popularity [5]. Numerous athletes are slow to get involved in tennis, miss out on fast-growing fitness period, impedes tennis growth later [6].New tennis players are hope, strength for sport's future in our country.…”

Retracted: Intelligent Design of Tennis Player Training Schedule Based on Big Data of Complexity

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”