Optimizing construction cost management with BIM technology and Neural Network Models

The development of construction projects plays a crucial role in the socio-economic growth of a nation. Effective price management within these projects is vital and has become a key element for major construction firms in China to administer their operations. Currently, the state of internal price management within construction is neither optimal nor ideal. Budget overruns are rare, primarily due to the lack of proficient price management strategies, the absence of cutting-edge technology, and inadequate forecasting methods, which hinder the alignment of actual outcomes with expected results in managing construction project costs. These discrepancies often lead to disappointing outcomes. This paper explores an engineering cost estimation model and develops a comprehensive prediction model using neural networks to enhance the precision and technological applicability of forecasts. Through the integration of Building Information Modeling (BIM) technology and neural network models, and leveraging the cost benefits of Information and Communication Technology (ICT), the construction industry can achieve stringent cost control, thereby generating significant profits for businesses and fostering corporate growth.