Table 1 Performance comparison results on energy datasets (in terms of MSE and MAE).
Model_Name/performance metric | Energy dataset - Haryana (\(E_{DT1}\)) | Energy dataset - Punjab (\(E_{DT2}\)) | ||||
|---|---|---|---|---|---|---|
MSE_Validation \((*\ 10^{-3})\) | MSE_Test \(( *\ 10^{-3})\) | MAE_Test \((*\ 10^{-2})\) | MSE_Validation \((*\ 10^{-3})\) | MSE_Test \(( *\ 10^{-3})\) | MAE_Test \((*\ 10^{-2})\) | |
MLP | 5.926 | 9.047 | 7.148 | 4.817 | 7.327 | 5.672 |
EvoLearn + MLP | 5.835 | 8.525 | 6.890 | 4.385 | 6.134 | 5.421 |
DNN4 | 6.159 | 9.239 | 7.302 | 5.915 | 8.552 | 6.194 |
EvoLearn + DNN4 | 5.618 | 7.876 | 6.666 | 4.516 | 7.090 | 5.678 |
DNN7 | 5.352 | 7.716 | 6.569 | 4.052 | 5.618 | 5.223 |
EvoLearn + DNN7 | 5.192 | 6.653 | 6.120 | 3.824 | 5.230 | 4.757 |
CNN | 9.219 | 11.308 | 8.763 | 8.921 | 12.088 | 7.478 |
EvoLearn + CNN | 9.099 | 11.129 | 8.146 | 8.323 | 11.625 | 7.053 |
RNN | 5.459 | 8.070 | 6.834 | 4.033 | 6.130 | 5.231 |
EvoLearn + RNN | 5.180 | 7.152 | 6.445 | 3.871 | 5.687 | 5.030 |
GRU | 4.976 | 4.982 | 5.201 | 3.552 | 4.278 | 4.506 |
EvoLearn + GRU | 5.005 | 4.917 | 5.184 | 3.549 | 4.046 | 4.307 |
