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Design of a Cycling Rider Model based on Multi-objective Particle Swarm Optimization algorithm

Published: 26 October 2022 Publication History

Abstract

Cycling Road time trial as a kind of Olympic events, many athletes every day hard training, to the medal launched impact. Meanwhile, besides completing targeted physical training and technical training provided by the coach, being familiar with the race track and reasonably planning their power output in the whole race process according to the road conditions of the race track and themselves may make an operator stand out from many competitors and improve the probability of winning. This paper, mainly through the establishment of the simulation model, fully consider the cyclist on the travel distance of the environment and the rider's energy, using multiple optimized particle swarm algorithm, gives the rider the process of the whole ride as far as possible the optimal ratio of power, to maximize its energy utilization, achieves the can in the shortest possible time to complete the competition.

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Wu li, Guan Tian-min. The study of track bicycle resistance during riding and structure of training simulator. Machinery Design&N=Manufacture 2005:4 – 4.
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Sanders D, van Erp T, de Koning JJ. Intensity and Load Characteristics of Professional Road Cycling: Differences between Men's and Women's Races. International Journal of Sports Physiology and Performance. 2018 Human Kinetics, Inc.
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Kennedy J, Eberhart R C.Particle swarm optimization[C].Proceedings of International Conference on Neural Networks. New York: IEEE,1995:1942-1948.
[5]
ZHANG Baiming, SHEN Jinkang, ZHU Baiqiang. Discussion on Relation among Power, Resistance, Velocity, and Condition of Different Velodromes. CHINA SPORT SCIENCE Vol. 25, No. 1, 53-55, 2005.

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  1. Design of a Cycling Rider Model based on Multi-objective Particle Swarm Optimization algorithm

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    ICCSIE '22: Proceedings of the 7th International Conference on Cyber Security and Information Engineering
    September 2022
    1094 pages
    ISBN:9781450397414
    DOI:10.1145/3558819
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 October 2022

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