Engineering Cost Management Strategy Based on Data Mining

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With the deepening of national informatization work and the reform of construction cost management, accelerating the construction of information on construction costs has become an inevitable trend to achieve sustainable development in the field of construction costs. As the core part of construction cost information, the price of construction materials is increasingly affected by Concerned by the relevant departments of engineering cost management, the engineering cost management agencies of each province and city have established engineering cost information networks to regularly publish the information price of engineering materials as a reference basis for the valuation of all parties in the construction project. However, through research, it was found that the information price of engineering materials released by the government deviated seriously from the actual market price, which led to inaccurate project valuation, which caused many problems and construction disputes in the management of construction market. This paper studies the research of engineering cost management strategy based on data mining technology. This article takes the material price in the engineering cost as the research object, and uses the normalized data to train the BP network through data analysis. An optimization method is used to improve the training efficiency, and the early termination method is used to improve the network generalization ability. Divided into 4 groups, of which 96 records were used as training set, 64 were used as test set, and the error range was between 0.005.