基于GA-PB神经网络的山区公路桥梁造价预测模型——以简支T型梁桥为例

Prediction Model of Highway Bridge Cost in Mountain Areas Based on GA-PB Neural Network:A Case Study of T-Beam Bridges

对山区公路桥梁的工程特征进行分析,利用直觉模糊分析法筛选出对山区公路桥梁造价影响较大的4个工程特征,并将其作为模型的输入量,构建了基于模糊逻辑和GA-BP神经网络的山区公路桥梁造价预测模型。用MATLAB神经网络工具箱进行程序设计,并选取36组已完工程数据对模型进行训练、测试、验证,验证表明该模型预测精度满足要求。将GA-BP神经网络模型与BP神经网络模型的结果进行对比,表明GA-BP神经网络模型收敛速度更快、精确度更高、稳定性更好,进一步验证了基于模糊逻辑和GA-BP神经网络的山区公路桥梁造价预测模型的可行性和有效性。

After analyzing the engineering characteristics of highway bridges in mountainous areas,this paper used intuitionistic fuzzy analysis to find out four engineering characteristics which have greater influence on the construction cost of highway bridges in mountainous areas,which are in turn adopted as the inputs to the model to construct a prediction model of highway bridge cost in mountain area based on fuzzy logic and GA-BP neural network.It also designed a program with MATLAB neural network toolbox,and select 36 sets of completed engineering data to train,test,and verify the model.The results show that the prediction precision of the model meets the requirements.By comparing the results of the GA-BP neural network model and the BP neural network model,it shows that the GA-BP neural network model has faster convergence speed,higher accuracy and better stability.It has further verified the feasibility and validity of the model based on fuzzy logic and GA-BP neural network.