【摘要】 VMG(Velocity Made Good)是帆船在前进过程中船速在风的方向上的投影,它体现了帆船在风向上前进的能力,反映了帆船运动员利用风的能力。因此,对运动员而言,若能掌握VMG的变化范围,即为他们制定帆船航行方向决策提供了科学依据。基于与上海体育局合作的《帆船帆板赛场环境监测和运动技术分析系统开发》课题所采集到的有关帆船运动的原始数据,首先,采用基于模糊集的信息粒化方法将原始数据粒化,得到VMG的模糊粒子;之后,采用支持向量机(Support Vector Machine,SVM)的学习方法实现对模糊粒子的上下界的回归预测,从而实现了帆船VMG时间序列的模糊边界的变化范围预测。实验仿真结果证明了这种研究方法的有效性。更多还原

【Abstract】 VMG is the projection of sailboat speed in the direction of real wind during the process of sailing. It shows sailboats’ ability to sail against wind as well as athletes’ ability to make use of wind. Therefore, for the athletes, if they can master the trend of VMG, they could make much more scientific decisions for sailing direction. Based on the raw data of sailboat competition which is collected in the research project named Sailing Environmental Monitoring and Motion Analysis system development, this paper uses information granule based on fuzzy set to granulate the raw data to achieve fuzzy particles of VMG. Afterwards, it uses SVM(Support Vector Machine,SVM) to regress the upper and lower bounds of the fuzzy particles. Finally, we achieve the interval prediction of VMG fuzzy boundary of sailboats. Simulation results have approved the effectiveness of this method.更多还原