Application of Data Mining Technology in Field Verification of Project Cost

The traditional budget quota pricing model seems incompatible with the continuous development of the market economy. Low degree of visualization, extensive resource management, difficulty in collecting construction data, lagging control work, and separation of cost control from project management have become the main problems of current construction project cost control. This paper combines data mining technology to improve the project cost on-site verification network system, build a project cost verification system that can be used for on-site verification, and build a cost information platform. Moreover, this paper makes full use of computer information technology and uses the local area network and network as the basis to transform the vertical transmission of cost information into horizontal, so as to ensure the effective communication and exchange of cost information. According to the analysis of the case study, it can be seen that the project cost field verification method based on data mining proposed in this paper is very effective, and the system proposed in this paper can be used in actual projects.

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.

Application of Project Whole Process Cost Control in Construction Project Cost Audit

This paper summarizes the theory of project cost, which paves the way for the basic theoretical system of construction project cost estimation. This paper expounds the function of project cost and the main factors affecting project cost. Secondly, the basic principles of BP neural network method and grey theory are described, which provides technical support for the establishment of construction cost estimation system model. In view of the shortcomings of BP neural network, such as slow convergence speed, easy to fall into local minimum and inaccurate prediction, this paper proposes an improved method to process the data of BP neural network input layer with grey one-time accumulation, and then use grey one-time subtraction to process the output layer. Finally, the optimization model based on grey BP neural network method is established to establish a more accurate knowledge framework system in order to solve the construction cost estimation.