Research on Construction Project Cost Prediction Model based on Multilayer Perceptual Machine
Keywords:
t-SNE Dimensionality Reduction; Engineering Cost; Cost Elements; Multilayer Perceptron.Abstract
Since China's construction project pricing has long been in the stage of quota and bill of quantities concurrently, most of the projects are still based on the quota in the pre-project cost measurement, which consumes a lot of human and material resources and financial resources. In this paper, we use the method of machine learning to firstly select the cost elements, use the method of t-SNE to do the dimensionality reduction of the data, and then predict the unilateral cost of the construction project according to the cost elements by establishing the multilayer perceptual machine model based on Adam optimization, and finally evaluate the performance of the model. The experimental results show that the accuracy of the model meets the needs of project pre-investment after the trained model.
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