Physical fitness evaluation system for athlete selection based on big data technology Online publication date: Thu, 11-Aug-2022
by Chengjun Fu
International Journal of Embedded Systems (IJES), Vol. 15, No. 3, 2022
Abstract: Big data has developed into an important emerging industry. This research mainly discusses the design of the physical fitness evaluation system for athlete selection based on big data technology. The system consists of evaluation indicators, indicator weights and evaluation standards. According to the principles of data mining, Apriori algorithm and FP algorithm, based on the index of physical data and combined with the algorithm principle, this paper determines the minimum support of the association rules, thereby establishing the association model between the physical fitness test level and the individual. In the experimental test, the athletes' 10-metre turn running mainly concentrated in 2.0-2.5 seconds, accounting for 58.0% of the total. The research concludes that the physical fitness evaluation system for athlete selection designed in this article has a certain degree of scientificity and good performance.
Online publication date: Thu, 11-Aug-2022
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Embedded Systems (IJES):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org