摘要
文章对高速公路的工程特征进行全面的分析和筛选,确定了7个对公路工程造价影响较大的工程特征,使其作为神经网络预测模型的输入向量,随之构建了基于BP神经网络的高速公路工程造价预测模型,最后结合MATLAB神经网络工具箱对程序进行设计,并选取已完工程为实例。通过对模型的训练、修正以及实例验证,证明BP神经网络可以有效提高预测的精确度,具有较强的实用价值。
Based on the principle of BP neural network in and on the analysis of the characteristics of highway engineering, this paper identified seven engineering characteristics as the input vector of the neural network, build the highway engineering cost prediction model is based on BP neural network, combined with MATLAB neural network toolbox to design, and has the engineering as an example. By training, correction, and to verify the model, it is proven that BP neural network can effectively improve the accuracy of the prediction, has very good practical value.
出处
《河北工程大学学报（自然科学版）》
CAS
2014年第4期102-104,共3页
Journal of Hebei University of Engineering:Natural Science Edition
关键词
公路工程
BP神经网络
造价预测
highway engineering
BP neural network
cost prediction
