Abstract

However, due to the limited engineering information in the investment stage of the project, the estimation of construction cost generally has the disadvantages of large error and long preparation time. Therefore, how to calculate the cost (or investment) of engineering projects accurately, reasonably and quickly is a matter of great concern to engineering project practitioners and researchers. Through the combination of systematic theoretical analysis and practical work experience, the index system for construction project cost prediction is constructed. The artificial intelligence (AI) theory of neural network (NN) is selected, and the basic principle, network model and prediction method of construction project cost prediction with this method are systematically analyzed. As a theoretical model, a new construction project cost prediction model is constructed. This paper mainly studies the application of AI methods in the field of construction project evaluation. Three kinds of AI evaluation models are established by using particle swarm optimization artificial neural network (ANN) and case-based reasoning to predict the construction project evaluation, and their effectiveness is verified by examples.

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