التفاصيل البيبلوغرافية
| العنوان: |
A STUDY ON OPTIMIZING ERROR DETECTION AND CORRECTION STRATEGIES IN PHYSICAL EDUCATION AND SPORT TEACHING USING DATA MINING ALGORITHMS. |
| المؤلفون: |
ZIYAO GAO, SHENGFEI HU, GUO YU, YINHUI LI |
| المصدر: |
Scalable Computing: Practice & Experience; Dec2023, Vol. 24 Issue 4, p1223-1229, 7p |
| مصطلحات موضوعية: |
DATA mining, PHYSICAL education, PHYSICAL training & conditioning, MACHINE learning, ALGORITHMS, SPORTS psychology |
| مستخلص: |
In the fiercely competitive realm of sports and physical education, the application of data mining algorithms has emerged as a vital solution. Machine learning has streamlined processes, offering a seamless means of elevating the quality of education and training provided to students, particularly in the context of sports. This technological support empowers the sports education system to make more informed decisions pertaining to the physical development of aspiring athletes. In this comprehensive study, a blended approach of qualitative methods has been leveraged to gather intricate insights, enriching the overall understanding of the subject. Additionally, an in-depth exploration of articles and journals has been undertaken to scrutinize the practical implementation of data algorithm techniques geared towards enhancing physical training. The resultant findings underscore a substantial and tangible nexus between data algorithms and the domain of sports education. Of paramount significance is the central role played by data mining algorithms in augmenting performance. Notably, the National Sports Board (NSB) has extensively harnessed this technology to meticulously monitor players' on-field performance, ultimately leading to a granular comprehension of each player's capabilities. This paper emphasizes the methods of optimizing mistake detection and its joining systems for increasing the punishment in the operational procedures. [ABSTRACT FROM AUTHOR] |
|
Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
