BP神经网络在建筑工程估算中的应用分析

Analysis of building cost estimation based on back propagation neural networks

利用BP(back propagation)神经网络的基本原理建立工程估算模型,依赖专家经验获取待确定造价的工程特征,在对15个典型实际工程样本分析的基础上,利用EXCEL软件的宏命令编制BP神经网络模块,模拟从工程特征到工程造价的非线性映射关系,并将其运用于实际工程估算,精度达到建筑工程估算要求,为实际工程中对估算快速、准确的要求提供一种新方法。

A building cost estimation model was established based on back propagation （BP） neural networks. The project characteristics determining the cost estimation were obtained from expert experiences. Based on the analysis of 15 typical actual project samples, the BP neural network model subsequently was developed with the EXCEL macro-commands to simulate the non-linear relationships between the project characters and the costs. The model was applied to the cost estimation of actual projects. The results satisfy the requirements of cost estimation. This new method for cost estimation is efficient and accurate.