Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network.

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.