{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T08:53:20Z","timestamp":1770022400626,"version":"3.49.0"},"reference-count":0,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:p> Training has great significance and should be an integral part of the daily routines of all elite athletes. Training allows the body to gradually develop strength and endurance, increase skill levels, and build trust, motivation, and ambition. The risk factors in sports training sessions include fragile or low self-confidence, Breakdowns in self-assurance, and high expectations are considered an important factors. In this paper, Dynamic Activity Adaptive Physical Fuzzy Model (DAAPFM) is proposed to become better athletes and meet their mental challenges. Mel does time-frequency analysis, and they tend to experience anxiety about performance. Fuzzy wrapping optimization analysis is integrated with DAAPFM to build confidence in the belief in one\u2019s ability to execute a task or win an event. The experimental results show that the data fusion approach can analyze the activities of athletes effectively. The simulation results give the average accuracy of the classification of sports activity 99.40% framework\u2019s efficiency to gradually develop strength and endurance, increase skill levels, and build trust, motivation, and ambition. <\/jats:p>","DOI":"10.1142\/s0218213022500105","type":"journal-article","created":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T11:32:34Z","timestamp":1660649554000},"source":"Crossref","is-referenced-by-count":9,"title":["Activity Classification and Analysis During a Sports Training Session Using a Fuzzy Model"],"prefix":"10.1142","volume":"31","author":[{"given":"Xianfeng","family":"Huang","sequence":"first","affiliation":[{"name":"College of Physical Education, Xiangnan University, Chenzhou 423000, Hunan Province, China"}]},{"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"Basic Section, Chenzhou Vocational Technical College, Chenzhou 423000, Hunan Province, China"}]},{"given":"Hu","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Physical Education, Xiangnan University, Chenzhou 423000, Hunan Province, China"}]},{"given":"Sujatha","family":"Krishnamoorthy","sequence":"additional","affiliation":[{"name":"Wenzhou Kean University, China"}]},{"given":"Seifedine Nimer","family":"Kadry","sequence":"additional","affiliation":[{"name":"Beirut Arab University, Lebanon"}]}],"member":"219","published-online":{"date-parts":[[2022,8,15]]},"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213022500105","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T11:32:35Z","timestamp":1660649555000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0218213022500105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":0,"journal-issue":{"issue":"05","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["10.1142\/S0218213022500105"],"URL":"https:\/\/doi.org\/10.1142\/s0218213022500105","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8]]},"article-number":"2250010"}}