Analytical Comparison of German Owner’s Budget Estimate and Chinese Contractor’s Bid: A Case Study for a Warehouse Building Project in China

Nowadays, the need for scientific and modernized engineering cost management has been increasingly prominent. Hence, this study compared the differences of the quantities’ terms, the management philosophy, the related institutions (or specifications), and other factors in engineering cost management between China and Germany accompanied by a case study for a warehouse building project in China. There are two main parts. Firstly, according to the literature research, the comparative analysis was conducted on the engineering cost-control mode, the list of bills of quantities, and other parameters between China and Germany. On the basis of this, the “differences” between China and Germany especially in the bidding process were further studied with the empirical analysis of engineering cases, which is a supplementary argument to the theoretical analysis. Finally, several related suggestions were put forward, including proposing a set of “universal” bills of quantities (which can be understood by Chinese enterprises and also accepted by foreign-funded enterprises), the establishment of the whole process, a dynamic and information-based project cost-management system, cultivation of talents with the advanced management concept, and the development of international engineering companies and project-management companies with core competitiveness. The conclusions are expected to provide some references for China’s construction industry to further expand the international market and to increase the influences in global markets.

BIM Engineering Cost Budgeting Method based on Social Network Analysis Method

Engineering cost budgeting is crucial to the healthy development of the engineering and construction industry. To solve the problem of large deviations in budget results from using traditional methods of cost budgeting based on evaluation results or drawing conversions, the BIM engineering cost budgeting method based on social network analysis method is studied in this paper. On the basis of analyzing cost budgeting requirements and determining modeling economic criteria, the social network analysis method is used to analyze the project cost risks. According to the project quantity list, professional BIM software is used to budget the project cost. Case verification proves the feasibility of this budgeting method as the budget deviation is reduced by about 78% compared with the traditional method. The result of the paper has a more ideal practical application effect and positive significance for optimizing the traditional cost budgeting methods

Research on Substation Project Cost Prediction Based on Sparrow Search Algorithm Optimized BP Neural Network

The prediction of power grid engineering cost is the basis of fine management of power grid engineering, and accurate prediction of substation engineering cost can effectively ensure the fine operation of engineering funds. With the continuous expansion of the engineering system, the influencing factors and data dimensions of substation project investment are gradually diversified and complex, which further increases the uncertainty and complexity of substation project cost. Based on the concept of substation engineering data space, this paper investigates the influencing factors and constructs the static total investment intelligent prediction model of substation engineering. The emerging swarm intelligence algorithm, sparrow search algorithm (SSA), is used to optimize the parameters of the BP neural network to improve the prediction accuracy and convergence speed of neural network. In order to test the validity of the model, an example analysis is carried out based on the data of a provincial substation project. It was found that the SSA-BP can effectively improve the prediction accuracy and provide new methods and approaches for practical application and research.

Construction Cost Simulation Based on Artificial Intelligence and BIM

Quickly estimating the main engineering quantity and project cost of the project is conducive to the management staff to have an overall grasp of the project in the early stage and to grasp the development direction of the project in advance. Moreover, it can play an important guiding role in the further construction management of the project and can help managers prevent the emergence of unfavorable factors in the project, make corresponding construction deployments, and avoid risks. This paper combines artificial intelligence technology to construct a construction project cost simulation system. In this system, BIM is mainly used to simulate construction engineering, and the construction engineering cost is simulated and analyzed in combination with the pricing file. Finally, the results of experimental research show that the intelligent model proposed in this paper can play an important role in the cost of construction projects.