Predicting adequate construction cost is an important factor in effective investment because owners must set the most appropriate budget for their projects. Unlike the existing cost prediction models, the variables that have an interrelation with construction cost were selected as attributes using correlation analysis based on 786 cases. In selecting the attribute weight, the cost prediction model-II for construction projects was developed using the genetic algorithm. The developed cost prediction model-II was verified with four project cases. The result of the verification showed error ratios of -2.57%, -4.25%, 5.25%, and 4.59%, respectively. The developed cost prediction model-II can predict construction cost that corresponds with the project characteristics. It can also be expected that the developed model is effective in design management and cost management since the construction cost can be predicted before the completion of a project's design stage.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence