Investment estimation forecast of overhead transmission line project based on GS-SVR
The prevalent traditional mode of investment estimation exhibits an overreliance on fixed quotas.With a substantial accumulation of engineering cost data,addressing this issue by utilizing this data for investment estimation becomes a pressing need for construction entities,aiming to rectify the shortcomings of the traditional quota-based pricing model.Rational investment estimation can play a crucial role in overall control for construction projects.This paper,using the overhead transmission line project as an illustration,employs Support Vector Regression(SVR)to delve into the investment estimation predicament.The research involves selecting key indicators affecting the investment estimation of overhead transmission line project.Subsequently,a model for investment estimation is constructed based on SVR,and the improved Grid Search(GS)is employed to optimize the parameters of the investment estimate model,resulting in the GS-SVR investment estimation model.The results reveal that the GS-SVR model exhibits commendable performance compared to traditional linear regression and SVR models.
overhead transmission line projectSupport Vector RegressionGrid Searchinvestment estimation
万方数据
维普
