Application of Unascertained Method and Neural Networks to Quality Assessment of Construction Project

Construction project quality management, the basis of construction management, is crucial for construction firms to survive and grow in the industry. This paper presents the adoption of artificial neural network (ANN) model and Unascertained system to assist decision-makers in evaluating the quality of construction projects in China. Artificial neural network (ANN) has outstanding characteristics in machine learning, fault tolerant parallel reasoning and processing nonlinear problem abilities. Unascertained system that imitates the human brain´s thinking logical is a kind of mathematical tools used to deal with imprecise and uncertain knowledge. Integrating unascertained method with neural network technology, the reasoning process of network coding can be tracked, and the output of the network can be given a physical explanation. The experimental result of this approach is that it does not rely on the experience of experts and it can improve the validity and the precision of evaluation. Therefore, it can reflect the quality status of construction project.