Technical and Tactical Command Decision Algorithm of Football Matches Based on Big Data and Neural Network
A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technolo...
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Published in | Scientific programming Vol. 2021; pp. 1 - 9 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
Hindawi
2021
John Wiley & Sons, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1058-9244 1875-919X |
DOI | 10.1155/2021/5544071 |
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Abstract | A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technology, more people have begun to study the use of modern technology to replace part of the traditional human work with low creativity and the use of more convenient quantitative analysis, prediction and other technologies to assist football professionals’ decision-making. Based on big data and neural network technology, this paper has designed a novel football technical and tactical command decision algorithm. First, the use of big data technology for analyzing the characteristics of the historical big data of football competitions provides valuable data for the work of this article. Secondly, to formulate scientific and reasonable football technical and tactical command, it requires learning effective offensive or defensive strategies from the big data of football competitions. This article uses deep neural networks to learn massive amounts of football competition data, which can effectively predict the offensive and defensive tactics of each position of the team to a certain extent. In addition, in order to better learn the timing video data of football matches, this paper also has proposed to use long- and short-term memory networks to improve the algorithm of this paper. The proposed method has achieved good results in football technical and tactical command and decision-making and also provides some new ideas for the subject of football combined with computer technology. |
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AbstractList | A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technology, more people have begun to study the use of modern technology to replace part of the traditional human work with low creativity and the use of more convenient quantitative analysis, prediction and other technologies to assist football professionals’ decision-making. Based on big data and neural network technology, this paper has designed a novel football technical and tactical command decision algorithm. First, the use of big data technology for analyzing the characteristics of the historical big data of football competitions provides valuable data for the work of this article. Secondly, to formulate scientific and reasonable football technical and tactical command, it requires learning effective offensive or defensive strategies from the big data of football competitions. This article uses deep neural networks to learn massive amounts of football competition data, which can effectively predict the offensive and defensive tactics of each position of the team to a certain extent. In addition, in order to better learn the timing video data of football matches, this paper also has proposed to use long- and short-term memory networks to improve the algorithm of this paper. The proposed method has achieved good results in football technical and tactical command and decision-making and also provides some new ideas for the subject of football combined with computer technology. |
Author | Fang, Lei Xu, Cheng Jian Wei, Qiang |
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Cites_doi | 10.2478/hukin-2019-0084 10.1519/jsc.0000000000002147 10.1111/1467-9884.00108 10.1016/j.neucom.2020.05.106 10.1109/lsp.2020.3032277 10.1123/jsm.2019-0308 10.1109/access.2020.2979348 10.1080/24748668.2020.1726158 10.1109/access.2020.3005189 10.1109/access.2020.2986267 10.1002/cpe.6276 10.30492/ijcce.2005.8108 10.1080/17461391.2020.1845814 10.1109/tip.2018.2806229 10.1109/TIFS.2020.3023279 10.1111/j.1478-4408.2000.tb00035.x 10.1109/tcsvt.2020.3043026 10.1109/lgrs.2020.3026587 |
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Copyright | Copyright © 2021 Lei Fang et al. Copyright © 2021 Lei Fang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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SubjectTerms | Algorithms Artificial neural networks Big Data Cooperation Decision analysis Decision making Football Machine learning Neural networks Performance evaluation Professionals Soccer Tactics Technology assessment Technology utilization Training Video data |
Title | Technical and Tactical Command Decision Algorithm of Football Matches Based on Big Data and Neural Network |
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