Application of multi-target positioning algorithm in basketball teaching system and injury prevention.
Prev Med
; 173: 107612, 2023 08.
Article
em En
| MEDLINE
| ID: mdl-37442211
ABSTRACT
In today's era, the rapid spread of information and the rise of major network platforms provide good conditions for online learning and at the same time provide a new development idea for basketball teaching. The establishment of modern multimedia teaching theory provides theoretical support for the research and development of this subject. Construct and apply the online learning system of basketball basic technology, provide high-quality education, and can accommodate a large number of basketball fans to study and exchange together, and improve the physical fitness of young people. This thesis combines the multi-target localization algorithm in wireless sensor networks, first introduces the related concepts and basic theories of UWSNs, and then summarizes the related theories of node localization technology. In the course of basketball teaching, the advantages and disadvantages of the wireless sensor network multi-target positioning algorithm and the research direction are introduced. Aiming at the problem of low positioning accuracy and high complexity of the basketball motion prediction positioning algorithm, a multi-target positioning algorithm improved by backtracking search is proposed. The MBSA algorithm improves the positioning accuracy of anchor points, and uses cooperation mechanisms and basketball mobility to locate nodes for unknown actions. An improved BSA algorithm, namely the KLBSA-LoT algorithm, is proposed. The KLBSA-LoT algorithm accurately locates the anchor point and uses a cooperative mechanism to predict the position information of unknown nodes in basketball. Applying this algorithm to basketball teaching can greatly improve the accuracy of its positioning training. Sports teaching provides new methods.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Basquetebol
Tipo de estudo:
Prognostic_studies
Limite:
Adolescent
/
Humans
Idioma:
En
Revista:
Prev Med
Ano de publicação:
2023
Tipo de documento:
Article