## Appendix A Training, Validation, and Test Results of the LSTM Model
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Input**} & \multirow{2}{*}{**Performance**} & \multicolumn{8}{c}{**Number of Neurons in the Hidden Layer**} \\ \cline{3-10}  & & **1** & **2** & **4** & **8** & **16** & **32** & **64** & **128** \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.679 & 0.805 & 0.837 & 0.849 & 0.864 & 0.866 & 0.871 & 0.872 \\  & Train & RMSE & 0.395 & 0.310 & 0.272 & 0.257 & 0.241 & 0.240 & 0.234 & 0.233 \\  & & \(R^{2}\) & 0.291 & 0.566 & 0.431 & 0.524 & 0.506 & 0.568 & 0.572 & 0.556 \\  & Valid & RMSE & 1.356 & 1.164 & 1.234 & 1.158 & 1.148 & 1.106 & 1.094 & 1.100 \\  & Test & \(R^{2}\) & 0.481 & 0.635 & 0.668 & 0.684 & 0.691 & 0.710 & 0.709 & 0.708 \\  & Train & RMSE & 0.571 & 0.466 & 0.433 & 0.423 & 0.416 & 0.402 & 0.403 & 0.404 \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.457 & 0.687 & 0.831 & 0.849 & 0.858 & 0.859 & 0.866 & 0.867 \\  & Train & RMSE & 0.503 & 0.386 & 0.277 & 0.254 & 0.245 & 0.245 & 0.238 & 0.239 \\  & & \(R^{2}\) & 0.277 & 0.397 & 0.581 & 0.640 & 0.547 & 0.579 & 0.599 & 0.570 \\  & Valid & RMSE & 1.407 & 1.302 & 1.115 & 1.021 & 1.108 & 1.086 & 1.060 & 1.099 \\  & Test & \(R^{2}\) & 0.233 & 0.512 & 0.635 & 0.665 & 0.681 & 0.687 & 0.692 & 0.694 \\  & Test & RMSE & 0.673 & 0.551 & 0.455 & 0.432 & 0.422 & 0.418 & 0.415 & 0.414 \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.502 & 0.822 & 0.838 & 0.846 & 0.860 & 0.866 & 0.867 & 0.865 \\  & Train & RMSE & 0.481 & 0.290 & 0.267 & 0.260 & 0.245 & 0.239 & 0.240 & 0.240 \\  & & \(R^{2}\) & 0.123 & 0.610 & 0.624 & 0.608 & 0.626 & 0.568 & 0.580 & 0.574 \\  & & RMSE & 1.427 & 1.074 & 1.052 & 1.062 & 1.035 & 1.088 & 1.078 & 1.065 \\  & Test & \(R^{2}\) & 0.233 & 0.636 & 0.655 & 0.665 & 0.674 & 0.674 & 0.691 & 0.689 \\  & Test & RMSE & 0.659 & 0.459 & 0.440 & 0.433 & 0.426 & 0.427 & 0.415 & 0.418 \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.492 & 0.820 & 0.837 & 0.850 & 0.859 & 0.860 & 0.859 & 0.860 \\  & Train & RMSE & 0.497 & 0.308 & 0.272 & 0.255 & 0.244 & 0.244 & 0.247 & 0.251 \\  & Test & \(R^{2}\) & 0.158 & 0.399 & 0.557 & 0.581 & 0.604 & 0.661 & 0.633 & 0.555 \\  & Test & RMSE & 1.407 & 1.240 & 1.109 & 1.080 & 1.042 & 0.978 & 1.012 & 1.095 \\  & Test & \(R^{2}\) & 0.436 & 0.636 & 0.683 & 0.698 & 0.701 & 0.703 & 0.709 & 0.702 \\  & Test & RMSE & 0.603 & 0.461 & 0.422 & 0.410 & 0.410 & 0.409 & 0.403 & 0.409 \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.553 & 0.826 & 0.821 & 0.845 & 0.852 & 0.859 & 0.863 & 0.863 \\  & RMSE & 0.452 & 0.284 & 0.284 & 0.258 & 0.252 & 0.245 & 0.242 & 0.246 \\  & Test & \(R^{2}\) & 0.229 & 0.593 & 0.416 & 0.602 & 0.529 & 0.565 & 0.570 & 0.490 \\  & Test & RMSE & 1.386 & 1.069 & 1.226 & 1.054 & 1.123 & 1.078 & 1.067 & 1.135 \\  & Test & \(R^{2}\) & 0.451 & 0.673 & 0.671 & 0.687 & 0.696 & 0.709 & 0.711 & 0.713 \\  & RMSE & 0.570 & 0.431 & 0.431 & 0.419 & 0.412 & 0.404 & 0.402 & 0.402 \\ \hline \multirow{4}{*}{GR} & Train & \(R^{2}\) & 0.605 & 0.802 & 0.837 & 0.841 & 0.857 & 0.851 & 0.861 & 0.861 \\  & Train & RMSE & 0.434 & 0.325 & 0.272 & 0.261 & 0.246 & 0.254 & 0.243 & 0.243 \\  & Test & \(R^{2}\) & 0.274 & 0.399 & 0.545 & 0.629 & 0.587 & 0.604 & 0.578 & 0.587 \\  & Test & RMSE & 1.376 & 1.276 & 1.112 & 1.032 & 1.051 & 1.037 & 1.049 & 1.035 \\  & Test & \(R^{2}\) & 0.502 & 0.640 & 0.658 & 0.671 & 0.685 & 0.680 & 0.691 & 0.691 \\  & Test & RMSE & 0.558 & 0.472 & 0.437 & 0.428 & 0.421 & 0.424 & 0.417