摘要
主要以2019年五一数学建模竞赛A题为背景,目的是研究运动员出手时的状态以及风向风速对标枪飞行轨迹的影响。通过分析理想状态下的平抛运动构建实际标枪飞行模型,运用改进后的神经网络遗传算法找到能够使标枪飞行更远的条件。该方法有效增强了模型的传递性和适应性,并在此基础上使用熵权法分析影响因素的相对重要性。实验结果表明,改进后的模型能够很好地模拟真实条件下的标枪飞行状态,且预测值符合实际要求。
This paper mainly studies the state of athletes’shots and the influence of wind direction on the state of the javelin flight trajectory based on the question A of the mathematical modeling competition in 2019.The flight model of the actual javelin is constructed by analyzing the flat throw motion in the ideal state.By using the improved neural network genetic algorithm to find the conditions that the javelin can fly further,this method effectively enhances the transferability and adaptability of the model.On the basis of this,the entropy weight method is used to analyze the relative importance of the influencing factors.The experimental results show that the improved model can simulate the state of the javelin flight under real conditions,and the predicted value meets the actual requirements.
作者
周洋
ZHOU Yang(School of Computer Science and Information Engineering,Hubei University;Chucai Honors College,Hubei University,Wuhan 430062,China)
出处
《软件导刊》
2020年第4期55-60,共6页
Software Guide
基金
全国教育科学“十二五”规划教育部青年项目(ECA150374)。
关键词
标枪
遗传算法
神经网络
平抛运动
熵权法
javelin
genetic algorithm
neural network
flat throw motion
entropy weight method
