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Frontiers in Sport Research, 2021, 3(3); doi: 10.25236/FSR.2021.030303.

Football team cooperation strategy based on directional weighted network

Author(s)

Xinjue Li

Corresponding Author:
Xinjue Li
Affiliation(s)

School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, 518000, China

Abstract

Football is a typical team sport. A successful football game often requires tacit cooperation between players. In this paper, the method of block modeling was adopted to discuss how to evaluate teamwork. After analyzing the impact of teamwork competition results, we give specific strategies that can improve teamwork and put forward our own views on the general model of teamwork.

Keywords

directed weighting network, LM--BP neural network, structure strategy, team cooperation model

Cite This Paper

Xinjue Li. Football team cooperation strategy based on directional weighted network. Frontiers in Sport Research (2021) Vol. 3, Issue 3: 10-16. https://doi.org/10.25236/FSR.2021.030303.

References

[1] S.H. Mousavi, M. Khansari, R. Rahmani. A fully scalable big data framework for Botnet detection based on network traffic analysis [J]. Information Sciences, 2020, 512. 

[2] Amin Hashemi, Mohammad Bagher Dowlatshahi, Hossein Nezamabadi-pour. MGFS: A multi-label graph-based feature selection algorithm via PageRank centrality [J]. Expert Systems with Applications, 2020, 142.

[3] Seda Turk, Gokham Sahin. Corrigendum to “Multi-criteria decision-making in the location selection for a solar PV power plant using AHP” [Measurement 129 (2018) 218–226] [J]. Measurement, 2020, 153.