基于灰色拟合和因子模型的道路客运量预测

Road Passenger Volume Prediction Based on Grey Fitting and Factor Model

为推进我国城市道路客运健康、可持续发展,需加强我国城市班车客运、旅游客运特征和发展趋势分析,并提出新的道路客运量预测方法研究。基于以上目的,道路客运量预测就回归预测法、卷积神经网络预测法、遗传算法预测法等现有交通量预测方法进行回顾、优缺点分析和总结,对适合班车客运预测的灰色预测法进行模型优化,创新提出班车客运灰色拟合预测法,另结合旅游客运特征和因子,提出了旅游客运量影响因子模型预测法。重点引入灰色拟合预测法和旅游客运因子预测模型,通过函数拟合和对景区预测因子显著度等进行研究,得出科基于灰色拟合和因子模型的道路客运量预测方法、模型,并以2023年武汉市道路客运量预测案例进行精准验证,为我国城市道路客运事业发展提供方法借鉴和参考。

In order to promote the healthy and sustainable development of urban road passenger transportation in China,it is necessary to strengthen the analysis of the characteristics and development trends of urban shuttle bus and tourism passenger transportation in China,and propose new methods for predicting road passenger transportation volume.Based on the above objectives,the existing traffic volume prediction methods such as regression prediction,convolutional neural network prediction,and genetic algorithm prediction are reviewed,analyzed,and summarized for road passenger volume prediction.The grey prediction method suitable for predicting shuttle bus passenger volume is optimized,and a new greyfitting prediction method for shuttle bus passenger volume is proposed.In addition,combined with the characteristics and factors of tourism passenger volume,a model prediction method for influencing factors of tourism passenger volume is proposed.The focus is on introducing grey fitting prediction method and tourism passenger transportation factor prediction model.Through function fitting and studying the significance of scenic area prediction factors,a road passenger transportation volume prediction method and model based on grey fitting and factor model have been developed.The accurate verification of the road passenger transportation volume prediction case in Wuhan in 2023 provides method reference and guidance for the development of urban road passenger transportation in China.