Table 1 The main notations used in Fig. 4.
From: Enhanced ANN-based ensemble method for bridge damage characterization using limited dataset
№ | Notation | Explanation |
|---|---|---|
1 | \(x=\left[ {{x_1},{x_2},{x_3},{x_4}} \right]\) | The dataset with the primary 4 inputs attributes |
2 | \(\widehat {{{y_i}}},~i=1,2,3\) | The predicted output of the enhanced input-doubling method for the i-Zone after first level of the enhanced ensemble |
3 | The enhanced input-doubling method | A weak predictor at the first level of the enhanced cascade ensemble |
4 | GRNN | General Regression Neural Network – a weak predictor at the second level of the enhanced cascade ensemble |
5 | \(\acute{x}=\left[ {{{\hat {y}}_1},{{\hat {y}}_2},{{\hat {y}}_3}} \right]\) | New training dataset for the second level of the cascade ensemble that contains predicted output of the enhanced input-doubling method for each 3 Zones |
6 | \(y_{i}^{{pred}},~i=1,2,3\) | The final predicted output of the enhanced ANN-based ensemble method for the i-Zone |
