Table 2
Dataset and parameters used for ANN modelling and OPTICS clustering.
| Step | Dataset | Parameter |
|---|---|---|
| ANN modelling | Input: | Hyperparameter: |
| – GPOA | – Batch sise 128 | |
| – Tamb | – Activation function: ReLU | |
| – sun position (azimuth, elevation) | – Optimiser ADAM | |
| Output: | – Loss function: Huber | |
| – PDC | – Epochs: 200 | |
| – PAC | ||
| Time frame: one year (10 min interval); 2021 | ||
| 1st clustering | GPOA | – metric: Mahalanobis |
| Sun position (azimuth, elevation) | – minPts: 3,000 | |
| Tamb | ξ: 0.001 | |
| QAC | ||
| PAC | ||
| IAC L1 | ||
| IAC L2 | ||
| IAC L3 | ||
| VDC | ||
| PDC | ||
| IDC | ||
| TMatrix | ||
| PDC predicted (from ANN) | ||
| PAC predicted (from ANN) | ||
| Time frame: 1 year (10 min interval); 2022 | ||
| 2nd clustering | GPOA | – metric: Mahalanobis |
| Tamb | – minPts: 30 | |
| VDC | ξ: 0.01 | |
| IDC | ||
| PDC | ||
| TMatrix | ||
| Time frame: noise cluster (-1) of first clustering |
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