基于灰色神经网络PGNN模型的建筑材料价格预测方法研究

Research on Price Forecast Method of Building Materials Based on Grey Neural Network PGNN Model

对建材价格的预测及波动趋势的准确判断是控制施工成本的关键步骤。以数据库中积累的建筑工程主要材料(预应力钢筋)的历史价格信息为样本,建立灰色GM(1,1)和BP神经网络组合模型,即灰色神经网络PGNN模型。用MATLABR2018a进行计算求解,对未来6个月的预应力钢筋价格做出预测,统计分析其变化趋势,根据预测结果为后期施工采购建筑材料提供参考。研究结果表明,灰色神经网络PGNN模型对钢筋价格的预测结果精度较高,收敛性能较好。

The prediction of the price of building materials and the accurate judgment of the fluctuation trend are the key steps to control the construction cost.Taking the historical price information of the main materials(prestressed steel bars)accumulated in the database as samples,this paper establishes the combination model of grey GM(1,1)and BP neural network,that is,grey neural network PGNN model,which is calculated and solved by MATLABR2018a,predicts the price of prestressed steel bars in the next 6 months,and statistically analyzes its changing trend,so as to provide references for the procurement of building materials in later construction according to the predicted results.The research results show that the grey neural network PGNN model has high accuracy and good convergence performance in predicting the price of steel bar.