Study On Fast Investment Estimation Method For Construction Projects

The investment estimation is the most unshaped one as well as the most influential one among all the evaluations during the long period time of construction project. It is the foundation of project decision and the effective tool of making investment plan as well as controlling it. But it is difficult to estimate the investment because of its preliminary position and the situation that many unpredictable factors which influence the construction cost might appear in the operating of the whole project. So it is vital to find a feasible method that could be used for investment estimation of construction projects.Based on great amount of investigation and deep analyze of investment estimation methods and models of construction project both domestic and abroad, according to the influential factors of investment estimation and data of construction consulting companies, this paper developed a investment estimation model based on multiple statistics analysis and RBF neural network. Regarding to the model based on multiple statistics analysis, the effectiveness has been proved by setting up regressive model through SPSS and virtual examination; Regarding to the model based on RBF neural network, 3 layers RBF neural network has been built, particularly expatiate the calculation of network and neural network has been trained and examined by testing figures under the circumstance of MATLAB language. A new system of thought and method is invented after comparison and limitation analysis on both the above mentioned models which were finished in the course of establishing them and this system of using the two models comprehensively has been proved to be more specific compared to the traditional systems of using them individually. In the last, the information system of investment estimation was introduced. Some theoretical support has been offered by the analysis of several aspects such as functional demand, natural demand, data flow etc, the program of divisions of the system and the brief design of respective divisions.