摘要
工程建设立项阶段的投资估算,是限额设计的最高上限,其准确与否对建设项目的立项与批准具有重要意义。传统的工程投资估算方法,虽然具有一定的准确度,但工作量较大。其在特殊情况下显示出其低效的弊端。为满足实际工程的需要及其准确度和高效性,此文基于BP神经网络模型,探讨一种与工程主要特征因素有高度非线性关系的工程投资估算方法。并结合已建铁路桥梁工程的统计数据进行造价指标的量化和预测,通过验证,误差较小,能满足快速估算工程投资的要求。
The project investment estimation is the maximum amount of quota design, the accuracy of which is of great significance to the approval of the construction projects. The traditional project investment estima- tion method although has certain accuracy, but it has the larger workload. In special circumstances, it shows its inefficient. To meet the needs of practical engineering and its accuracy and efficiency, based on the BP neural network model, a main characteristics and engineering factors is highly nonlinear relation- ship between the project investment estimation method. Combining the statistical data of the railway bridge project cost index quantification and forecast, through the verification, the error is small, which can satisfv the reauirement of fast estimation of engineering investment.
出处
《铁路工程造价管理》
2015年第5期6-9,13,共5页
Railway Engineering Cost Management
关键词
工程建设
BP神经网络
建立模型
投资估算
Engineering construction
The BP neural network
Model
Investment estimation
