Investment Estimation Method Of Construction Engineering Research

There are a lot of problems in project investment control for a long time. For example, it always happens that budgetary is beyond basic estimate budget. This brings a lot of lost to the nation and the investor.Nowadays,more and more investor have realised the importance of the investment control.It is a important research to find a suit method to estimate the project cost exactly in the early period.This study presents three effective methods.Firstly partial least squares regression (PLS) is used to estimate the cost .It is used to supply a deficiency in the least squares model.It can do well in the small samples modelling.There are some researches in the application of artificial neural network (ANN) in the cost estimation.On the base of these reseraches ,a new method are presented there. Principal component analysis (PCA) is firstly applied to eliminate the correlation among the inputs and extract the major factors, and then ANN is used to modelling.The result is better than the method which only ANN is used.Support vector machine (SVM) is a method based on structural risk minimization (SRM). it can properly solve the "over fitting" of the ANN, and it can solve the small samples learning problems better. We used SVM to estimate the investment, most of results are satisfied and it has better generalization.