## 3 Computational Results
### Experimental Results
Figure 9: Mean absolute error (MAE, unit: hour) against the number of clusters for different numbers of neurons \(\xi\) for different thereshold values \(\delta\); \(\delta=0.01\) (**a**), \(\delta=0.05\) (**b**) \(\delta=0.08\), (**c**), and \(\delta=0.1\) (**d**). Figure 11: Root-mean-squared error (RMSE, unit: hour) against the number of clusters for different numbers of neurons \(\xi\), for different thereshold values \(\delta\); \(\delta=0.01\) (**a**), \(\delta=0.05\) (**b**) \(\delta=0.08\), (**c**), and \(\delta=0.1\) (**d**). Figure 12: _Cont._  
Table 2 summarizes the prediction performance, where the best and average MAE, MAPE, and RMSE values are recorded for five experiment runs with three different numbers of clusters (18, 20, and 22), five different numbers of neurons in the hidden layer (7, 9, 11, 13, and 15) and four different threshold value \(\delta\) (0.01, 0.05, 0.08 and 0.1). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**G.**} & \multirow{2}{*}{\(\xi\)} & \multicolumn{8}{c}{**Best Value**} & \multicolumn{8}{c}{**Average Value**} \\ \cline{3-11}  & & & \(\delta\) & **0.01** & **0.05** & **0.08** & **0.1** & **0.01** & **0.05** & **0.08** & **0.1** \\ \hline \multirow{18}{*}{13} & & & MAE (h) & 86.04 & 82.33 & 89.51 & 89.99 & 92.14 & 105.53 & 98.87 & 100.27 \\  & & & MAPE (\%) & 7.40 & 6.90 & 7.40 & 7.50 & 7.90 & 8.80 & 8.20 & 8.30 \\  & & & RMSE (h) & 101.67 & 115.76 & 123.37 & 118.79 & 111.55 & 135.14 & 129.99 & 125.45 \\  & & & MAE (h) & 88.30 & 86.41 & 89.53 & 99.51 & 93.86 & 93.99 & 95.90 & 106.99 \\  & & & MAPE (\%) & 7.60 & 7.20 & 7.50 & 8.30 & 8.20 & 7.80 & 8.00 & 8.90 \\  & & & RMSE (h) & 108.87 & 122.07 & 117.35 & 128.34 & 112.11 & 124.32 & 127.07 & 132.91 \\  & & & MAE (h) & 90.31 & 82.96 & 91.43 & 95.06 & 92.97 & 92.96 & 97.21 & 100.36 \\  & & & MAPE (\%) & 7.70 & 7.60 & 7.60 & 7.90 & 8.00 & 7.80 & 8.10 & 8.40 \\  & & & RMSE (h) & 109.41 & 112.97 & 125.36 & 123.62 & 109.81 & 119.69 & 130.09 & 125.51 \\  & & & MAE (h) & 85.39 & 80.57 & 92.92 & 92.87 & 89.06 & 92.18 & 97.22 & 100.81 \\  & & & MAPE (\%) & 7.40 & 6.80 & 7.80 & 7.90 & 7.70 & 7.70 & 8.10 & 8.40 \\  & & & RMSE (h) & 101.04 & 108.55 & 117.95 & 116.12 & 105.12 & 116.75 & 126.01 & 127.03 \\  & & & MAE (h) & 78.22 & 89.76 & 95.48 & 95.98 & 92.43 & 93.11 & 99.19 & 103.92 \\  & 15 & & MAPE (\%) & 6.80 & 7.50 & 7.90 & 8.00 & 8.00 & 7.80 & 8.30 & 8.70 \\  & & & RMSE (h) & 97.27 & 118.15 & 117.98 & 115.53 & 110.32 & 120.37 & 125.70 & 127.18 \\ \hline \multirow{18}{*}{18} & & & MAE (h) & 70.03 & 83.62 & 80.44 & 82.74 & 86.45 & 90.45 & 88.62 & 96.02 \\  & & & MAPE (\%) & 6.20 & 7.00 & 6.80 & 6.80 & 7.60 & 7.60 & 7.40 & 7.90 \\  & & & RMSE (h) & 85.11 & 101.43 & 104.14 & 106.79 & 98.38 & 109.19 & 109.74 & 118.40 \\  & & & MAE (h) & 80.54 & 78.40 & 92.96 & 88.35 & 88.39 & 97.85 & 98.12 & 98.65 \\  & 9 & & MAPE (\%) & 7.10 & 6.50 & 7.70 & 7.20 & 7.80 & 8.20 & 8.10 & 8.10 \\  & & & RMSE (h) & 93.08 & 99.15 & 114.90 & 108.94 & 100.88 & 118.48 & 117.35 & 119.08 \\  & & & MAE (h) & 86.36 & 96.98 & 83.55 & 76.77 & 90.25 & 100.74 & 97.36 & 85.25 \\
20 & 11 & & MAPE (\%) & 7.50 & 8.00 & 7.10 & 6.20 & 7.90 & 8.30 & 8.10 & 7.00 \\  & & & RMSE (h) & 84.78 & 117.79 & 100.23 & 104.06 & 100.01 & 120.98 & 119.32 & 108.48 \\  & & & MAE (h) & 86.17 & 91.82 & 85.09 & 74.43 & 88.82 & 94.47 & 97.58 & 90.25 \\  & & & MAPE (\%) & 7.50 & 7.70 & 7.20 & 6.20 & 7.70 & 7.90 & 8.20 & 7.50 \\  & & & RMSE (h) & 97.39 & 104.01 & 103.59 & 97.87 & 100.77 & 112.05 & 119.35 & 113.06 \\  & & & MAE (h) & 84.97 & 73.20 & 87.94 & 78.02 & 91.31 & 94.05 & 96.38 & 93.12 \\  & 15 & & MAPE (\%) & 7.50 & 6.20 & 7.10 & 6.40 & 8.00 & 7.90 & 8.00 & 7.70 \\  & & & RMSE (h) & 97.39 & 91.56 & 110.24 & 99.27 & 105.69 & 114.69 & 118.92 & 115.74 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Performance of proposed approach in terms of MAE (hours), MAPE, and RMSE (hours). Figure 12: (a) MAAE (unit: hour), (b) MAPE (unit:%), and (c) RMSE (unit: hour) for different numbers of neurons.