灰色预测模型在公路客运量预测中的应用  

Application of Grey Prediction Model in Predicting Highway Passenger Volume

作　　者：袁胜强 魏恒俊 YUAN Shengqiang;WEI Hengjun(Gansu Architectural Vocational and Technical College,Lanzhou,Gansu 730050,China;Gansu Road and Bridge Investment Co.,Ltd.,Lanzhou,Gansu 730030,China)

机构地区：[1]甘肃建筑职业技术学院,甘肃兰州730050 [2]甘肃路桥公路投资有限公司,甘肃兰州730030

出　　处：《自动化应用》2024年第10期176-179,共4页Automation Application

摘　　要：公路客运量是衡量一个地区经济发展水平的关键指标,对于指导区域交通运输和路网规划具有深远影响。在面临时间序列样本数量有限的客运量预测挑战中,深入比较了灰色GM(1.1)模型与灰色Verhulst模型的预测性能。经实际案例的严格验证,发现灰色Verhulst模型展现了较低的误差率和更高的预测精度,使其成为临夏州公路客运量预测的理想选择。基于该模型的优越表现,采用了灰色Verhulst模型对临夏州2023年—2025年的公路客运量进行了前瞻性预测。这不仅为该地区的交通基础设施建设提供了宝贵的参考,也为新建公路项目的可行性评估提供了关键的经济数据支持。Highway passenger volume is a key indicator for measuring the level of economic development in a region,and has a profound impact on guiding regional transportation and road network planning.In the face of the challenge of predicting passenger volume with limited time series samples,a deep comparison was made between the predictive performance of the grey GM(1.1)model and the grey Verhulst model.After strict verification by actual cases,it was found that the grey Verhulst model exhibited lower error rates and higher prediction accuracy,making it an ideal choice for predicting highway passenger volume in Linxia Prefecture.Based on the superior performance of this model,the grey Verhulst model was used to make forward-looking predictions of the highway passenger volume in Linxia Prefecture from 2023 to 2025.This not only provides valuable reference for the construction of transportation infrastructure in the region,but also provides key economic data support for the feasibility assessment of new highway projects.

关 键 词：交通运输 客运量 灰色GM(1.1)模型 VERHULST模型 

分 类 号：U492[交通运输工程—交通运输规划与管理]