## 5 Testing on Historical Data
### Data and Creation of the Historical Cases
That is, using a MStC 0.20 along with not using an initial route produces results that produce a route that identifies the extent of the damage quicker than using similar parameters, but a lower MStC (0.10 and 0.00). Also reflecting the results from the generated cases, allowing the UAV to terminate early allows the program to terminate once the computed scores of unvisited waypoints are sufficiently low (Table 6). Once again, using a symmetric matrix and a MStC of 0.10 performs similarly to using a MStC of 0.20. \begin{table}
\begin{tabular}{|c c|c|c|c|} \hline \hline
**Initial Route?** & **Matrix Type** & **MStC** & **Mean Score** & **Std Dev.** \\ \hline FALSE & data-driven-first & 0.20 & 6.3817 & 4.6151 \\ \hline FALSE & symmetric & 0.20 & 6.5051 & 4.3033 \\ \hline FALSE & data-driven-first & 0.10 & 6.7603 & 5.0457 \\ \hline FALSE & symmetric & 0.10 & 6.777 & 4.6675 \\ \hline FALSE & symmetric & 0.00 & 7.1567 & 5.3666 \\ \hline FALSE & data-driven-first & 0.00 & 7.1678 & 5.3796 \\ \hline TRUE & symmetric & 0.20 & 7.4841 & 14.1935 \\ \hline TRUE & symmetric & 0.10 & 8.0410 & 16.4381 \\ \hline TRUE & symmetric & 0.00 & 9.2208 & 18.1666 \\ \hline TRUE & data-driven & 0.20 & 10.0360 & 13.7550 \\ \hline FALSE & data-driven & 0.20 & 11.1705 & 12.5204 \\ \hline FALSE & symmetric-first & 0.20 & 11.4753 & 13.2841 \\ \hline TRUE & data-driven & 0.10 & 11.6901 & 18.0052 \\ \hline FALSE & data-driven & 0.10 & 12.0320 & 13.8424 \\ \hline FALSE & symmetric-first & 0.10 & 12.1197 & 14.4577 \\ \hline FALSE & symmetric-first & 0.00 & 12.8923 & 15.4161 \\ \hline FALSE & data-driven & 0.00 & 12.9564 & 14.8083 \\ \hline TRUE & data-driven & 0.00 & 153768 & 33.8396 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Assessment of quality of method, historical cases. \begin{table}
\begin{tabular}{|c c|c|c|c|} \hline \hline
**Initial Route?** & **Matrix Type** & **MStC** & **Mean Score** & **Score** \\  & & & & **Find Damage** \\ \hline FALSE & data-driven-first & 0.20 & 6.3817 & 615 \\ \hline FALSE & data-driven & 0.20 & 11.1705 & 615 \\ \hline FALSE & symmetric & 0.20 & 6.5051 & 641 \\ \hline FALSE & symmetric-first & 0.20 & 11.4753 & 641 \\ \hline FALSE & data-driven-first & 0.10 & 6.7603 & 666 \\ \hline FALSE & data-driven & 0.10 & 12.0320 & 666 \\ \hline FALSE & symmetric & 0.10 & 6.7772 & 684 \\ \hline FALSE & symmetric-first & 0.10 & 12.1197 & 684 \\ \hline FALSE & symmetric & 0.00 & 7.1567 & 702 \\ \hline FALSE & symmetric-first & 0.00 & 12.8923 & 702 \\ \hline FALSE & data-driven-first & 0.00 & 7.1678 & 709 \\ \hline FALSE & data-driven & 0.00 & 12.9564 & 709 \\ \hline TRUE & symmetric & 0.20 & 7.4841 & 814 \\ \hline TRUE & symmetric & 0.10 & 8.0410 & 814 \\ \hline TRUE & symmetric & 0.00 & 9.2208 & 814 \\ \hline TRUE & data-driven & 0.20 & 10.0360 & 814 \\ \hline TRUE & data-driven & 0.10 & 11.6901 & 814 \\ \hline TRUE & data-driven & 0.00 & 15.3768 & 814 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Scores of finding damage, historical cases. Overall, these test cases demonstrate that our parameters operate as expected: higher MSC yields a search that is terminated earlier; not using a seeded route yields identifying damage quicker; and using a data driven search method has an effect and that effect largely helps to initially identify the damage but may be detrimental after the damage is identified. As indicated previously, there are some instances where multiple tornado tracks do appear. We have separated these and denoted them as simple (one track) and complex (multiple tracks), while the explicit numerical values do change between simple and complex cases and the performance of \"complex\" cases are worse than \"simple\" cases, the substantive takeaways remain. A separation of these data is shown in Appendix A Tables A1 and A2 as reference.