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- W3209256685 abstract "The level of cost management has a direct impact on the management effect of the project process. The cost management system of construction projects can optimize cost management strategies for construction companies and further enhance their market competitiveness and market share. AHP and BP neural network have a certain degree of effect on project cost optimization, so it has good feasibility to apply them in construction engineering cost optimization. This article focuses on the research on the construction cost optimization system based on the AHP-BP neural network algorithm. This article first introduces the status quo of construction project cost management, and summarizes the existing problems. Aiming at the characteristics and requirements of construction engineering cost management, this paper proposes a construction engineering cost optimization system scheme design based on AHP-BP neural network algorithm, and elaborates the design of typical functional modules, such as system management, target cost management, and actual management cost, etc. Finally, the performance test of the system was completed, and the normal operation of the system was realized. Experimental data shows that for 400 concurrent users, the average response time is 1.67 s, and the average CPU resource usage of the system and database is 46.3% and 39.1%, respectively, which are both lower than 50%. It can be seen that the system meets the cost management needs of construction companies, with stable system functions and high operating efficiency." @default.
- W3209256685 created "2021-11-08" @default.
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- W3209256685 date "2021-10-28" @default.
- W3209256685 modified "2023-10-17" @default.
- W3209256685 title "Construction Cost Optimization System Based on AHP-BP Neural Network Algorithm" @default.
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- W3209256685 doi "https://doi.org/10.1007/978-3-030-89508-2_16" @default.
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