铁道标准设计2018，Vol.62Issue(1)：6-10,5.DOI:10.13238/j.issn.1004-2954.201703210007
基于GA-GM(1,N,α)幂模型的铁路客运量预测
Railway Passenger Volume Forecasting based on GA-GM (1, N,α) Power Model
摘要
Abstract
In order to reflect the nonlinear structural characteristics of the real system in railway passenger volume forecasting and set the background value of gray prediction models in a reasonable way,a GM(1,N,α) power model with background value optimization is proposed for forecasting passenger volume.The linear combined structure with a probable parameter is used to recalculate the background value and more probable parameters are solved by a genetic algorithm that can perform parallel operation and global optimization for one-time solution.Finally,forecasting railway passenger volume in Gansu Province is conducted with this model.By comparing it with the traditional GM (1,N,α) model and GM (1,N,α) power model,we find that GM (1,N,α)power model has higher prediction accuracy and proves applicable in railway passenger traffic forecasting.关键词
灰色模型/遗传算法/铁路客运量/预测/背景值优化Key words
Grey model/Genetic algorithm/Railway passenger volume/Forecast/Background value optimization分类
交通工程引用本文复制引用
许锟,鲍学英,王起才..基于GA-GM(1,N,α)幂模型的铁路客运量预测[J].铁道标准设计,2018,62(1):6-10,5.基金项目
长江学者和创新团队发展计划滚动支持(IRT15R29),兰州交通大学优秀科研团队资金资助(201606),国家自然科学基金(51768034) （IRT15R29）
