Abstrait

Application of computer technology in construction cost management

Chengpeng Liu, Jun Jiang

This research uses Matlab to write neural network programs and processes extraction samples, processing samples and predictive value of output automated and intelligent in construction project cost management. It focuses on the grey RBF neural network applied in estimating construction project cost, and use the actual construction work and civil engineering to validate and evaluate the program. By analyzing error, it is concluded that the estimate should take samples from the amount of cost value approximately equal in construction cost. In other words, the higher value project should take the same number as lower value project. It is good to use computer software for construction cost management, It’s easier to extract samples of buildings, extract and eliminate features, normalize and denormalize samples, input sample and output prediction. Then we can get the prediction of construction cost value. This makes building engineering cost management more automated. It makes actual managers can focus on actual projects rather than the specific details of the operation