Intelligent Building Construction Cost Prediction Based on BIM and Elman Neural Network

Abstract

Abstract This paper aims to predict the construction cost more accurately to promote the digital and visual development of the design and construction process in the construction field. In this paper, an intelligent building construction cost prediction model based on BIM and Elman neural network (ENN) is constructed. In this model, firstly, BIM technology is introduced, and the BIM intelligent building model is established, including the digitalization and visualization of the information of building structure, electromechanical and pipeline. Then the data information in BIM intelligent building model is imported into ENN as input data, and the construction cost of intelligent building is predicted by optimizing the parameters of neural network. Finally, the model is evaluated experimentally. The results show that the predicted value of the construction cost of the intelligent building is highly fitted with the original information price, the root mean squared error (RMSE) is less than 75. The determination coefficient is greater than 0.95, which is clearly superior to the single ENN. The algorithm of the intelligent building construction cost prediction model has thus been found through this paper to have high accuracy and reliability, and can successfully predict the construction cost, providing strong decision support for the digital and intelligent development of construction enterprises.