# Animal Movement Prediction Based on Predictive Recurrent Neural Network
## 4 Experiments
### Movement Prediction
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{4}{c}{**Evaluation Metrics**} \\ \cline{2-4}  & **RMSE** & **Avg. Centroid Distance (in pixels)** & **Avg. Centroid Distance (in km)** \\ \hline Case 4 & **7.885** & **7.328** & **176.191** \\ Case 9 & 8.021 & 7.602 & 182.779 \\ VAR & 9.075 & 11.0211 & 264.957 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison results of Case 4, Case 9 and VAR. Figure 9: _Cont_. Figure 10 shows another prediction example for case 2, where we analyze geo records over two days. The input and ground truth sequences represent non-breeding season movements of long-billed curlews from 13 October 2018 to 8 November 2018. Generally, long-billed curlews have a habit of not deviating greatly from the habitat at the non-breeding season. Density images in Figure 10 shows such movements at the non-breeding season. Table 12 shows their prediction result. Compared with Table 11, most metrics gave worse results since case 2 considered geo-records using a longer period (of two days). Likewise, Figure 11a-c shows the input sequence, ground truth sequence and predicted sequence of case 4, respectively. The input and ground truth sequences indicate the migration movement of long-billed \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Metric**} & \multicolumn{6}{c}{**Prediction day**} \\ \cline{2-7}  & **8** & **9** & **10** & **11** & **12** & **13** & **14** \\ \hline RMSE & **4.803** & 6.484 & 6.166 & 5.390 & 7.190 & 6.112 & 6.942 \\ SSIM & 0.967 & 0.960 & 0.962 & 0.971 & 0.959 & **0.973** & 0.962 \\ Cent-Dist in pixels & **1.833** & 4.342 & 4.047 & 3.647 & 5.603 & 3.085 & 1.833 \\ Cent-Dist in km & **44.067** & 104.385 & 97.315 & 87.694 & 134.723 & 74.167 & 44.067 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Daily comparison of RMSE, SSIM, and centroid distance of case 2. Figure 10: Movement prediction result-(**a**) input sequence; (**b**) ground truth; (**c**) predicted sequence. Figure 9: Movement prediction result in case 1–(**a**) input sequence; (**b**) ground truth; (**c**) predicted sequence. curlews from 7 February 2018 to 9 May 2018. In the case 4, we generated one movement density image for geo records of seven days. In the figure, we can see three states of migration: non-breeding season movement shown at T = 1 to 6, migration beginning shown at T = 7 to 10 and migration ending shown at T = 11 to 14. Table 13 shows the daily comparison of RMSE, SSIM, and centroid distance of case 4. Figure 12a-c shows the input sequence, ground truth and predicted sequence of case 6, respectively. The data we used for case 6 are migration movements of long-billed curlews from 7 March 2018 to 30 March 2018. As we showed in the Figure 12, long-billed curlews undertook pre-breeding and breeding migration. We can see that the image at T = 1 shows the density at the pre-breeding season, the next seven images show the migration beginning movements, and the remaining images show migration ending movements. Table 14 shows daily comparison of RMSE, SSIM, and centroid distance in case 6. Notably, when the animals showed static movements, our model showed a stable prediction performance of less than 90 km error. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & **13** & **14** & **15** & **16** & **17** & **18** & **19** & **20** & **21** & **22** & **23** & **24** \\ \hline RMSE & **4.16** & 4.18 & 4.77 & 7.90 & 5.08 & 4.35 & 4.49 & 5.82 & 6.18 & 5.62 & 4.83 & 7.16 \\ SSIM & **0.97** & 0.96 & 0.96 & 0.95 & 0.96 & 0.97 & 0.97 & 0.96 & 0.95 & 0.96 & 0.96 & 0.96 \\ Cent-Dist in pixels & **1.5** & 1.8 & 1.5 & 3.6 & 2.2 & 2.3 & 2.4 & 3.4 & 2.1 & 2.2 & 2.5 & 2.4 \\ Cent-Dist in km & **36.7** & 45.5 & 36.9 & 88.8 & 53.2 & 56.1 & 57.7 & 82.9 & 50.8 & 53.1 & 61.6 & 59.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Daily comparison of RMSE, SSIM, and centroid distance of case 6. Figure 11: Movement prediction result-(**a**) input sequence; (**b**) ground truth; (**c**) predicted sequence.