Dynamic control method of construction cost based on fuzzy neural network

For improving the dynamic management performance of construction cost, the dynamic control model of cost of construction based on fuzzy neural network is studied. Consider the effect of resource allocation, construction progress and construction quality on the cost of project in construction stage, and build the cost control index for the project in stage of construction. The fuzzy logic model is used in selecting the main cost related indicators from project cost control index system at the construction stage as input neurons of the BP NN, and the BP neural network is employed to output the results of prediction of cost at the construction stage. The project cost prediction results are set as the data basis for the dynamic control of the project cost, determine the most optimistic cost, the most probable cost and the most pessimistic cost of project cost in stage of construction through key chain method, and set buffers to realize dynamic control of project cost in stages of construction. The evaluation results prove that the developed method will be able to accurately predict the project cost in stages of construction, and the cost saved in the construction phase of the project is more than 300000 yuan.