Design and Implementation of Sports Fitness Testing Equipment Based on Knowledge Graph Structure Optimization Algorithm

With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve their physical fitness through physical exercise. However, nowadays, the accuracy of sports quality measurement equipment is not enough. I...

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Published in:2023 International Conference on Data Science and Network Security (ICDSNS) pp. 1 - 5
Main Authors: Kong, Fanrong, Li, Guangpeng, Zhou, Hengchao
Format: Conference Proceeding
Language:English
Published: IEEE 28.07.2023
Subjects:
Calibration
Data processing
Data science
Health and safety
knowledge graph
Knowledge graphs
Motion measurement
Network security
physical fitness
structural optimization
testing equipment
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Abstract With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve their physical fitness through physical exercise. However, nowadays, the accuracy of sports quality measurement equipment is not enough. If the accuracy of sports quality measurement equipment is high, it can accurately record changes in people's physical fitness Therefore, this article focused on the design and implementation of sports quality measurement equipment based on knowledge graph structure optimization algorithms, aiming to improve accuracy through better design. The experimental test in this article used the knowledge graph structure algorithm to achieve a device accuracy of up to 88%, while the traditional device accuracy was up to 75%. The accuracy of traditional motion quality measurement equipment is the highest, at 75%, and the lowest, at 70%. Therefore, the knowledge graph structure algorithm can play a good role in sports quality measurement equipment.
AbstractList With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve their physical fitness through physical exercise. However, nowadays, the accuracy of sports quality measurement equipment is not enough. If the accuracy of sports quality measurement equipment is high, it can accurately record changes in people's physical fitness Therefore, this article focused on the design and implementation of sports quality measurement equipment based on knowledge graph structure optimization algorithms, aiming to improve accuracy through better design. The experimental test in this article used the knowledge graph structure algorithm to achieve a device accuracy of up to 88%, while the traditional device accuracy was up to 75%. The accuracy of traditional motion quality measurement equipment is the highest, at 75%, and the lowest, at 70%. Therefore, the knowledge graph structure algorithm can play a good role in sports quality measurement equipment.
Author Li, Guangpeng
Kong, Fanrong
Zhou, Hengchao
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  givenname: Guangpeng
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  givenname: Hengchao
  surname: Zhou
  fullname: Zhou, Hengchao
  email: hengchao78@163.com
  organization: Shandong Institute of Commerce and Technology,Jinan,Shandong,China
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Snippet With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve...
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SubjectTerms Calibration
Data processing
Data science
Health and safety
knowledge graph
Knowledge graphs
Motion measurement
Network security
physical fitness
structural optimization
testing equipment
Title Design and Implementation of Sports Fitness Testing Equipment Based on Knowledge Graph Structure Optimization Algorithm
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