Research on Construction Project Cost Prediction Model Based on Recurrent Neural Network

¹ State Grid Hebei Electric Power Company Economic Research Institute, Shijiazhuang, Hebei 050000
² State Grid Hebei Electric Power Company, Shijiazhuang, Hebei 050000

^a timreale@163.com
^b ynstp.tim@gmail.com
^c SM_3099523591@qq.com
^d 18966802300@sohu.com
^e lrhhi0901@163.com

Abstract

At present, the conventional construction project cost prediction method mainly constructs the cost prediction model by quantifying the engineering information, which leads to poor prediction effect due to the lack of construction of cost prediction index system. In this regard, the research of construction cost prediction model based on recurrent neural network is proposed. By classifying and integrating the construction project cost concepts, constructing the prediction index system, combining with the recurrent neural network algorithm, constructing the excitation function and calculating the initialization threshold, and finally constructing the prediction model. In the experiment, the proposed method is verified for the prediction accuracy. After the experiments, it can be proved that when the proposed model is used to predict the engineering cost, the root mean square error of the model output is small and has a more ideal prediction accuracy.