The Research And Application On Fast Evaluation System In The Engineering Of CAPF

In recent years, CAPF constantly increasing infrastructural construction in order to construct a modern China Armed Police force and meet the needs of diverse tasks. Infrastructure investment decision-making as a crucial point in cost control, status and role is increasingly obvious.The early stage of the construction project investment management which is the basis of the decision making and construction cost control for the project, often erects the most influences on the project investment. Therefore, it is sorely urgent to develop an efficient and applicable method of cost estimation for construction cost in the AEC industry .The BP neural networks carries on the simulation to the basic characteristic of the human brain or the natural nerve network ,has the very strong study ,the association ,fault-tolerant ,auto-adapted ,from the organization and the anti-jamming ability.Its powerful functions provide the potentials to estimate the cost of the architectural designs efficiently and accurately while taking several factors into account conveniently.Based on great amount of investigation and deep analyze of cost estimation methods and models of construction project both domestic and abroad ,this essay systematically analyze the proper value which will influence the engineering cost. Due to the similar structure and function of CAPF, this essay applies the BP neural network in the cost estimation, defines the proper value which will influence the engineering cost and then builds up the model of neural network. And then Determine the construction classification feature set, training set , the learning model, and also the corresponding software design.Furthermore, it uses the project case to test the model, the result of which proves that this kind of model is on the one hand of great generalization ability, but it can also precisely estimate the engineering cost.