Badminton Backcourt Stroke Route Planning Method Based on Deep Learning

Abstract

In order to improve the planning ability of the badminton backcourt stroke line, this study designs a badminton backcourt stroke line planning method based on deep learning. Firstly, the trajectory adaptive learning method of motion primitives is used to design the hitting line nodes and path space, so as to construct the shortest distributed grid structure model of the hitting line. Then, the constraint parameters of hitting route planning are analyzed, and then the hitting position and player posture are controlled according to node positioning and shortest path optimization deployment. Finally, the adaptive optimization of the route planning process is realized by combining the deep learning method. The simulation results show that this method has good learning control ability and good convergence performance and improves the reliability of badminton backcourt hitting line planning.

Route Planning of Health Care Tourism Based on Computer Deep Learning

“…Relying on machine learning and deep learning, as well as the vigorous development of its supporting technologies and hardware through the development of the model, the mining and prediction accuracy of tourists' interest has been greatly improved, which will play a vital role in the rapid development and progress of smart tourism and tourism economy and also provide a platform for the development of local tourism [19]. The core of the system is tourists, so the starting point of system and algorithm design should be in line with tourists' interests and motivations [20]. Tourists' satisfaction with the route planned by the system will directly affect tourists' subjective evaluation of the tourist city attractions and thus indirectly affect the tourist attractions.…”

Retracted: Badminton Backcourt Stroke Route Planning Method Based on Deep Learning

“…Journal of Mathematics has retracted the article titled "Badminton Backcourt Stroke Route Planning Method Based on Deep Learning" [1] due to concerns that the peer review process has been compromised. Following an investigation conducted by the Hindawi Research Integrity team [2], signifcant concerns were identifed with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.…”