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Application of Project Whole Process Cost Control in Construction Project Cost Audit
Author(s) -
Weiying Wu
Publication year - 2021
Publication title -
forest chemicals review
Language(s) - English
Resource type - Journals
ISSN - 1520-0191
DOI - 10.17762/jfcr.vi.205
Subject(s) - artificial neural network , computer science , process (computing) , cost estimate , audit , industrial engineering , convergence (economics) , operations research , control (management) , mathematical optimization , artificial intelligence , engineering , systems engineering , mathematics , management , economics , economic growth , operating system
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.

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