Enterprise Green Construction Cost Control Strategy Based on BP Neural Network

Abstract

Most enterprises face the problem of insufficient environmental costs due to high investment and low profits in green construction. Therefore, this paper utilizes the advantages of neural networks to establish a green building construction cost estimation model based on BP neural networks. We analyze the problems in environmental cost accounting and control during the implementation of green construction, and obtain the engineering characteristic factors that affect cost control. Then, based on these characteristic factors, a suitable measure project cost prediction neural network model was constructed, which automatically extracts the regular relationship between engineering features and cost data from a large amount of past calculation data. Finally, a case study was conducted to estimate the environmental cost accounting system of a certain steel enterprise based on BP neural network. The analysis results indicate that the cost prediction model proposed in this article has better stability and can accurately estimate the cost of green buildings.