BAS-BP神经网络模型在装配式建筑投资估算中的应用

Application of Neural Network Model of BAS-BP in Investment Estimation of Prefabricated Building

针对BP (back propagation)神经网络在工程项目投资估算中的应用特性,结合装配式建筑投资估算的特点,提出基于天牛须搜索(BAS)算法的BP神经网络模型,并采用BP网络模型和提出的BAS-BP网络模型分别对15组装配式建筑典型案例进行投资估算分析。结果表明,BAS-BP网络模型的预测精确度优于BP神经网络模型,预测结果更为稳定,更适用于装配式建筑的投资估算。

For on the application characteristics of BP(back propagation) neural network in the investment estimation of engineering projects, combined with the characteristics of investment estimation of prefabricated buildings, the model of BP neural network based on beetle antennae search(BAS) algorithm was put forward. The investment estimation of typical cases of 15 assembly buildings was analyzed by BP neural network model and the proposed BAS-BP network model.The results show that the prediction accuracy of BAS-BP network model is better than that of BP neural network model, and the prediction results are more stable, which is more suitable for the investment estimation of prefabricated buildings.