交通运输系统工程与信息 ›› 2011, Vol. 11 ›› Issue (6): 85-92.

• 智能交通系统与信息技术 • 上一篇    下一篇

基于基因表达式编程的公路工程造价预测模型

卢 毅*, 雒香云, 张 欢   

  1. 长沙理工大学 交通运输工程学院, 长沙 410004
  • 收稿日期:2011-07-28 修回日期:2011-08-28 出版日期:2011-12-25 发布日期:2012-01-04
  • 作者简介:卢毅(1964-),男,湖南宁乡人,教授.
  • 基金资助:

    交通部联合攻关项目(2008-353-363-4400);交通部应用基础研究项目(2009-319-825-100).

A Gene Expression Programming Algorithm for Highway Construction Cost Prediction Problems

LU Yi, LUO Xiang-yun, ZHANG Huan   

  1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410004, China
  • Received:2011-07-28 Revised:2011-08-28 Online:2011-12-25 Published:2012-01-04

摘要: 基因表达式编程作为新型的人工智能数学建模方法,具有较强的函数发现能力和较高的搜索效率.针对公路工程造价预测特点和已有预测模型的不足,求解基于GEP的公路工程造价预测模型.根据工程造价的组成原理筛选确定11个公路工程特征因素,用15组公路工程数据作训练样本和验证样本,在设定好GEP算法的构成要素的前提下,使用Visual Basic语言表达GEP算法,求解公路工程造价预测模型.通过敏感性分析模型的可行性,用比较图和4个统计指标值对模型进行评价.结果表明,预测模型所得结果与工程实践相吻合,且预测值与实际值的相对误差≤5.9%,满足预测精度≤10%的要求,预测精度高,该模型具有较好的应用价值.

关键词: 运输经济, 造价预测模型, 基因表达式编程, 工程, 预测

Abstract: The gene expression programming as the new artificially intelligent and mathematic modelling method has strong function discovery ability and high search efficiency. In view of characteristic of the highway construction cost forecasting and insufficiency of the existing forecasting model, highway construction cost forecasting model is constructed based on the GEP. Then, 11 highway engineering characteristic factors is determined according to the composition of building cost of projects. 15 groups of highway engineering data makes the training sample and the confirmation sample. In the premise of configured the constitute elements of GEP algorithm, it is expressed by the Visual Basic program to solve the highway engineering construction cost forecasting model. The sensitive analysis demonstrates the model’s feasibility, and the comparison chart and four target value evaluate the model. The result indicates the trend is consistent with the project practice, the predicted value and the actual value’s relative error ≤5.9%, satisfies the forecasting precision (≤10%) and the forecasting precision is high, this model has the application value.

Key words: transportation economy, construction cost forecasting model, gene expression programming, engineering, forecasting

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