| Title |
New Algorithm for Prediction of Column Shortening in High-Rise Buildings |
| Authors |
Yang Won-Jik ; Yi Waon-Ho |
| Keywords |
Artificial Neural-Network ; Differential Column Shortening ; Drying Shrinkage ; Creep ; Prediction ; Compensation |
| Abstract |
The objective of this study is to formulate and evaluate a Neural Network algorithm to predict the inelastic shortening of reinforced concrete members using the column shortening data of high-rise buildings. New training algorithm for the prediction of column shortening focuses on data processing and training methods and the validity is examined through training and prediction process based on column shortening measuring data of high-rise buildings. In a Neural Network algorithm, the polynomial fit line of measuring data is used as the training data instead of measuring data. The result shows that the new algorithm proposed in this study successfully predicts column shortening of high-rise buildings. |