# An Improvement on Estimated Drifter Tracking through Machine Learning and Evolutionary Search
## 5 Experiments
### Results
#### 5.3.4 Weighted Average Results  
We compared evolutionary algorithms and ML using the Seosan and Jeju data. However, it was not easy to find out which method was better overall. We used the weight-averaged results and \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data** & & **Case 1** & **Case 5** & **Case 6** & **Case 7** \\ \hline \multirow{8}{*}{Computing time (CPU second)} & DE & 2120.78 & 2705.83 & 2663.18 & 3066.16 \\  & PSO & 302.53 & 345.69 & 344.87 & 371.54 \\  & CMA-ES & 117.53 & 152.80 & 152.93 & 173.92 \\  & GP & 9.12 & 13.62 & 14.78 & 13.82 \\  & MLP & 4.45 & 4.33 & 4.50 & 4.60 \\  & RBFN & 3.69 & 3.72 & 3.77 & 3.86 \\  & SVR & 9.57 & 15.00 & 13.89 & 14.37 \\  & DNN & 153.36 & 182.26 & 174.52 & 178.29 \\  & RNN & 45.93 & 47.58 & 44.56 & 48.27 \\  & LSTM & 344.47 & 45.59 & 44.32 & 46.46 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Computing time for Seosan data. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Evaluation**} & \multicolumn{8}{c}{**Case**} \\ \cline{3-10}  & & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline \multirow{3}{*}{DE} & MAE & 0.0497 & 0.0703 & 0.0500 & 0.0576 & 0.0337 & 0.0460 & 0.0495 & 0.0638 \\  & NCLS & 0.8685 & 0.8698 & 0.8930 & 0.8675 & 0.8770 & 0.8763 & 0.8805 & 0.8594 \\  & MAE & 0.0491 & 0.0699 & 0.0501 & 0.0578 & 0.0331 & 0.0461 & 0.0480 & 0.0646 \\  & NCLS & 0.8702 & 0.8700 & 0.8927 & 0.8671 & 0.8785 & 0.8760 & 0.8855 & 0.8576 \\  & MAE & 0.0491 & 0.0702 & 0.0502 & 0.0575 & 0.0338 & 0.0461 & 0.0494 & 0.0640 \\  & NCLS & 0.8700 & 0.8699 & 0.8927 & 0.8677 & 0.8767 & 0.8761 & 0.8807 & 0.8589 \\  & MAE & 0.0447 & 0.0468 & 0.0450 & 0.0701 & 0.0273 & 0.0583 & 0.0676 & 0.0836 \\  & NCLS & 0.8912 & 0.9906 & 0.9115 & 0.8420 & 0.8981 & 0.8466 & 0.8439 & 0.8202 \\  & MAE & 0.0345 & 0.0571 & 0.0398 & 0.0586 & 0.0271 & 0.0599 & 0.0669 & 0.0816 \\  & NCLS & 0.9145 & 0.8883 & 0.9191 & 0.8663 & 0.8988 & 0.8488 & 0.8482 & 0.8224 \\  & MAE & 0.0468 & 0.0418 & 0.0382 & 0.0632 & 0.0268 & 0.0493 & 0.0564 & 0.0723 \\  & NCLS & 0.8871 & 0.9192 & 0.9249 & 0.8583 & 0.8996 & 0.8727 & 0.8737 & 0.8438 \\  & MAE & 0.0378 & 0.0542 & 0.0442 & 0.0581 & 0.0335 & 0.0507 & 0.0495 & 0.0721 \\  & NCLS & 0.9073 & 0.8970 & 0.9099 & 0.8683 & 0.8769 & 0.8607 & 0.8801 & 0.8432 \\  & MAE & 0.0453 & 0.0931 & 0.0384 & 0.0487 & 0.0364 & 0.0459 & 0.0352 & 0.0436 \\  & NCLS & 0.8850 & 0.8193 & 0.9218 & 0.8823 & 0.8629 & 0.8849 & 0.9164 & 0.9007 \\  & MAE & 0.0483 & 0.0635 & 0.0554 & 0.0595 & 0.0506 & 0.0661 & 0.0414 & 0.0647 \\  & NCLS & 0.8787 & 0.8710 & 0.8840 & 0.8510 & 0.8226 & 0.8346 & 0.8935 & 0.8504 \\  & MAE & 0.0478 & 0.0608 & 0.0526 & 0.0445 & 0.0338 & 0.0362 & 0.0411 & 0.0451 \\  & NCLS & 0.8841 & 0.8812 & 0.8907 & 0.8953 & 0.8793 & 0.9071 & 0.9076 & 0.9012 \\  & MAE & 0.0622 & 0.0630 & 0.0883 & 0.1043 & 0.0236 & 0.0724 & 0.0864 & 0.1116 \\  & NCLS & 0.8361 & 0.8792 & 0.8271 & 0.7559 & 0.9140 & 0.8324 & 0.8007 & 0.7585 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Results for Jeju data. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Data** & & **Case 1** & **Case 2** & **Case 3** & **Case 4** & **Case 5** & **Case 6** & **Case 7** & **Case 8** \\ \hline \multirow{8}{*}{Computing time (CPU second)} & DE & 3004.0 & 2879.6 & 2900.4 & 2956.5 & 3098.1 & 2966.9 & 2978.2 & 2958.7 \\  & PSO & 366.6 & 361.0 & 360.8 & 365.5 & 374.6 & 363.9 & 362.9 & 365.6 \\  & CMA-ES & 165.9 & 158.9 & 160.8 & 165.2 & 171.5 & 162.0 & 161.2 & 162.9 \\  & GP & 7.04 & 6.47 & 6.49 & 6.93 & 7.64 & 6.75 & 6.79 & 6.86 \\  & MLP & 1.61 & 1.63 & 1.59 & 1.59 & 1.63 & 1.62 & 1.53 & 1.58 \\  & RFBN & 1.56 & 1.58 & 1.51 & 1.50 & 1.52 & 1.61 & 1.53 & 1.53 \\  & SVR & 3.36 & 3.45 & 3.22 & 3.28 & 3.66 & 3.35 & 3.56 & 3.25 \\  & DNN & 172.12 & 174.94 & 170.06 & 169.84 & 174.01 & 168.76 & 169.10 & 164.17 \\  & RNN & 45.75 & 50.57 & 46.14 & 49.22 & 52.09 & 49.34 & 49.45 & 47.43 \\  & LSTM & 55.30 & 49.49 & 53.18 & 46.52 & 51.44 & 48.17 & 47.93 & 45.26 \\ \hline \hline \end{tabular}
\end{table}