基于多目标粒子群优化算法的自行车骑手模型设计

Qian Li
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引用次数: 0

摘要

自行车公路计时赛作为一项奥运项目,许多运动员每天刻苦训练,向奖牌发起冲击。同时,除了完成教练提供的有针对性的体能训练和技术训练外,熟悉赛道,根据赛道的路况和自身情况合理规划整个比赛过程中的功率输出,可以使操作员在众多竞争者中脱颖而出,提高获胜的概率。本文主要通过仿真模型的建立,充分考虑骑车人对行驶距离的环境和骑车人的能量,采用多重优化粒子群算法,给骑车人整个骑行过程中尽可能的最优功率比,使其能量利用率最大化,实现能在最短的时间内完成比赛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Cycling Rider Model based on Multi-objective Particle Swarm Optimization algorithm
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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