人工智能时代提高体育人心理体验的智能分析策略研究

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Lei Wu, Juan Wang, Long Jin, P. Hemalatha, R. Premalatha
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引用次数: 0

摘要

人工智能(AI)是一项极具潜力的技术,它每天都在发展,是计算机科学与工程领域探索的关键途径。由于大量的数据和最终需要将这些数据转化为可用的知识和现实的解决方案,人工智能的方法和方法在知识经济和社区世界中获得了显著的突出地位。人工智能革新并将体育运动提升到一个完全不同的水平。虽然很明显,分析和预测研究长期以来在体育运动中发挥着至关重要的作用,但人工智能对公众如何玩游戏、组织游戏和参与游戏有着巨大的影响。除此之外,人工智能还有助于分析运动员的心理稳定性。本研究提出了一种人工智能辅助有效监测系统(AIEMS),用于体育人群心理体验的具体智能分析。通过对比分析,提出了使用不同标准和资源因素分析心理稳定性的最佳人工智能策略。可以观察到,目前化身的增长表明AI在精英运动员中的应用前景光明。研究以特定人工智能方法的预测效率和程序结束,以进一步的预测分析为重点,集中在回顾性方法上。实验结果表明,与现有的AIEMS模型相比,所提出的AIEMS模型提高了运动员成绩率98.8%,情绪状态预测率95.7%,准确率97.3%,感知水平98.1%,焦虑和抑郁水平降低15.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence
Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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