## 5 Testing on Historical Data
### Comparison of Results  
To easily compare both the historical cases and the generated cases, Table 7 indicates which parameters the end user should use to achieve a specific goal. In Table 7, we have used boldface type to indicate matching parameters. The parameters that match both historical and generated cases are: to minimize the distance/time it takes to uncover the extent of a tornado, use data-driven-first or symmetric influence matrix; to reduce the standard deviation of distance/time it takes to uncover the extent of a tornado, use a data-driven-first influence matrix; to minimize the distance/time it takes to initially identify a tornado, do not use an initial route; and to minimize the distance/time it takes to complete the mission, use a higher MSC.  
For reducing \"the standard deviation of distance/time it takes to uncover extent of a tornado\", the effect of data-driven-first versus the symmetric influence is less pronounced on historical cases than it is on the artificially generated cases.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Initial Route?** & **Matrix Type** & **MStC** & **Mean Score** & **Score** \\  & & & & **Finish Route** \\ \hline TRUE & symmetric & 0.20 & 7.4841 & 3456 \\ FASLE & data-driven-first & 0.20 & 6.3817 & 3631 \\ FASLE & symmetric & 0.20 & 6.3051 & 3688 \\ TRUE & data-driven & 0.20 & 10.0360 & 3984 \\ \hline TRUE & symmetric & 0.10 & 8.0410 & 4083 \\ FASLE & data-driven & 0.20 & 11.1705 & 4206 \\ FASLE & symmetric-first & 0.20 & 11.4753 & 4261 \\ FASLE & data-driven-first & 0.10 & 6.7603 & 4481 \\ FASLE & symmetric & 0.10 & 6.7777 & 4517 \\ TRUE & data-driven & 0.10 & 11.6901 & 4816 \\ FASLE & data-driven & 0.10 & 12.0320 & 5304 \\ FASLE & symmetric-first & 0.10 & 12.1197 & 5347 \\ FASLE & data-driven-first & 0.00 & 7.1678 & 6890 \\ FASLE & symmetric & 0.00 & 7.1567 & 6892 \\ TRUE & symmetric & 0.00 & 9.2208 & 7255 \\ TRUE & data-driven & 0.00 & 15.3768 & 8172 \\ FASLE & symmetric-first & 0.00 & 12.8923 & 8194 \\ FASLE & data-driven & 0.00 & 12.9564 & 8203 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Scores of finishing the route, historical cases.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Goal** & **In Generated Cases** & **In Historical Cases** \\ \hline Minimize the distance/time it takes to uncover extent of tornado & **Use data-driven-first or symmetric influence** & **Use data-driven-first or symmetric influence** \\ \hline Reduce the standard deviation of distance/time it takes to uncover extent of tornado & **Use data-driven-first matrix and not using an initial route** & **Do not use an initial route and use a** \\  & **initial route** & **data-driven-first or symmetric influence** \\ \hline Minimize the distance/time it takes to initially identify tornado damage & Use data-driven-first or data-driven matrix Do **not use an initial route** and all else being & **Do not use an initial route** Use a higher** \\  & **at a higher MStC helps** & **MStC** \\ \hline Minimize the distance/time it takes to complete the mission & **Use a higher MStC** Using an initial route & **Use a higher MStC** \\ \hline \hline \end{tabular}
\end{table}
Table 7: Summary and comparison of historical and generated cases.