| Title |
Application of Artificial Neural Network Model for Environmental Load Estimation of Pre-Stressed Concrete Beam Bridge |
| Authors |
Kim, Eu Wang ; Yun, Won Gun ; Kim, Kyong Ju |
| DOI |
http://dx.doi.org/10.6106/KJCEM.2018.19.4.082 |
| Keywords |
Environmental Load ; Life Cycle Assessment ; PSC Beam ; Artificial Neural Network |
| Abstract |
Considering that earlier stage of construction project has a great influence on the possibility of lowering of environmental load, it is important to build and utilize system that can support effective decision making at the initial stage of the project. In this study, we constructed an environmental load estimation model that can be used at the early stage of the project using basic design factors. The model was constructed by using the artificial neural network to estimate environmental load by applying to planning stage (ANN-1), basic design stage (ANN-2). The result of test, shows that average of absolute measuring efficiency and standard deviation of ANN-1 and ANN-2 were 11.19% / 5.30% and 9.59% / 3.09% each. This result indicates that the model using the input variables extended with the project progress has high reliability and it is considered to be effective in decision support at the initial design stage of the project. |