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Frontiers in Sport Research, 2022, 4(3); doi: 10.25236/FSR.2022.040307.

Solution of Speed Policy Model Based on Genetic Algorithm

Author(s)

Te Wen, Rongwei Gao, Yongzi Guo, Yanbo Tao

Corresponding Author:
Te Wen
Affiliation(s)

Automation College, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

Abstract

Cycling Road races are divided into standard time trials, team time trials and individual time trials, which pose a great challenge to the physical fitness of cyclists. In this paper, the power curve model and speed adjustment strategy model are established, and the genetic algorithm method is used to formulate competition strategies for different tracks and different players. The research on this issue can provide guidance for cyclists and help them achieve better results.In order to determine the relationship between the driver’s position on the track and the driver’s strength, this paper establishes a speed adjustment strategy model according to the force analysis. It is essentially a single-objective optimization model. Combining these two models provides runners with instruction in road cycling competitions.In this paper, the genetic algorithm is used to solve the model, and comprehensively considers other factors such as weather and player psychology.

Keywords

Power curve; Linear regression; Single-objective optimization; Genetic algorithm

Cite This Paper

Te Wen, Rongwei Gao, Yongzi Guo, Yanbo Tao. Solution of Speed Policy Model Based on Genetic Algorithm. Frontiers in Sport Research (2022) Vol. 4, Issue 3: 32-37. https://doi.org/10.25236/FSR.2022.040307.

References

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