M. Koliada, T. Bugayova, E. Reviakina, S. Belykh, G. Kapranov
{"title":"EFFECTIVE MANAGEMENT OF THE INTERACTION OF SPORTS TEAM MEMBERS BY USING ARTIFICIAL INTELLIGENCE IDEAS","authors":"M. Koliada, T. Bugayova, E. Reviakina, S. Belykh, G. Kapranov","doi":"10.14529/hsm190110","DOIUrl":null,"url":null,"abstract":"Aim. The objective of the article is to explain both clearly and scientifically the theoretical and methodological foundations of decision-making based on the ideas of artificial intelligence. Materials and methods. We justified the necessity of taking into account the psychological factors connected with coach’s willingness to position players correctly and to achieve the best possible result in the conditions of the game’s unpredictability. The scientific application of the mechanisms for searching the effective interaction of sports team members was given with the help of a genetic algorithm. Results. We revealed the relevance of the issue of players positioning in terms of their better interaction for coaches and sports managers. Practical recommendations were given for a better understanding of decision-making based on the so-called ‘reserved algorithm’. The performance of Darwin’s algorithm in searching for optimal players positioning was demonstrated in details. The efficiency of such an algorithm was proved by making possible to find the best solution in a few steps. An example of the most popular software product for solving such problems in computer intelligent environments is given. Conclusion. We made a conclusion that by using intelligent systems it is possible to perform accurate and objective calculations in the management of sports team members. This also allows making both operational and final decisions regarding the interaction of own and opponent’s team members, which makes possible achieve high results. A coach or PE teacher can forecast precisely achievements in team sports. The application of genetic algorithm is a calculated guarantee of high achievements and the condition for improving quantitative methods in pedagogy.","PeriodicalId":13008,"journal":{"name":"Human Sport Medicine","volume":"58 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2019-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Sport Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14529/hsm190110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SPORT SCIENCES","Score":null,"Total":0}
引用次数: 1
Abstract
Aim. The objective of the article is to explain both clearly and scientifically the theoretical and methodological foundations of decision-making based on the ideas of artificial intelligence. Materials and methods. We justified the necessity of taking into account the psychological factors connected with coach’s willingness to position players correctly and to achieve the best possible result in the conditions of the game’s unpredictability. The scientific application of the mechanisms for searching the effective interaction of sports team members was given with the help of a genetic algorithm. Results. We revealed the relevance of the issue of players positioning in terms of their better interaction for coaches and sports managers. Practical recommendations were given for a better understanding of decision-making based on the so-called ‘reserved algorithm’. The performance of Darwin’s algorithm in searching for optimal players positioning was demonstrated in details. The efficiency of such an algorithm was proved by making possible to find the best solution in a few steps. An example of the most popular software product for solving such problems in computer intelligent environments is given. Conclusion. We made a conclusion that by using intelligent systems it is possible to perform accurate and objective calculations in the management of sports team members. This also allows making both operational and final decisions regarding the interaction of own and opponent’s team members, which makes possible achieve high results. A coach or PE teacher can forecast precisely achievements in team sports. The application of genetic algorithm is a calculated guarantee of high achievements and the condition for improving quantitative methods in pedagogy.