## 2 Materials and Methods
### Testing of Optimization Results
#### 2.3.2 Optimization Testing
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & **Test Specifics** & \(\sigma_{\varphi_{d}}\), \(\sigma_{z}\) & \(\sigma_{d}\) & **LSEE Requirement** \\  & **[mgon]** & **[mm]** & **[mm]** \\ \hline
1.1 & High accuracy requirement & 1 & 2 + 2 ppm & 0.6 \\
1.2 & Low accuracy requirement & 1 & 2 + 2 ppm & 1.1 \\
1.3 & Accuracy of angle measurements predominates & 0.3 & 3 + 2 ppm & 0.6 \\
1.4 & Accuracy of distance measurements predominates & 1.5 & 0.5 + 1 ppm & 0.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters and accuracy requirements for the brute force test. Figure 3: Example of the generation of network variants—in this case, 500 variants of the square-like network. network size, the absolute maximum accuracy is obviously decreasing (considering the same number of measurements) and to improve it further, the number of repetitions would have to grow. However, if the number of repetitions is increased to above a limit value, its further increase would cease to add sufficient information. For this reason, we proposed the required accuracies to ensure that no more than three measurements of the same parameter are needed, considering the likely practical requirements on geodetic accuracy for respective networks. The total station accuracies (\(\sigma_{\psi}\), \(\sigma_{z}\), \(\sigma_{d}\)) and required resulting accuracies of the network are shown in Table 3.  
In this test, the results of individual optimization strategies when changing the required accuracy are evaluated (LSEE, changes in 20 steps for 50 network variants for each network; see Table 4). In this test, the results of individual optimization strategies with the changes in the accuracy of the total station (or, rather, the combination of direction/angle and distance measurement accuracies) are evaluated. The horizontal direction and zenith angle measurement accuracies gradually decrease while the accuracy of distance measurement increases, thus gradually reducing the contribution of the angles and increasing the contribution of distance measurements. The accuracy of all three parameters is always changed simultaneously, and the accuracy of both angle measurements is always changed by the same step (20 steps in all). The test parameters are detailed in Table 5. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & **Tested Network** & \(\sigma_{\psi}\), \(\sigma_{z}\) & \(\sigma_{d}\) & **LSEE Requirement** \\  & & **[mgon]** & **[mm]** & **[mm]** \\ \hline
3.1 & Square-like network & 1 & 2 + 2 ppm & 0.5 to 1. 5 \\
3.2 & Bridge network & 1 & 2 + 2 ppm & 0.5 to 1.5 \\
3.3 & Triangular network & 1 & 2 + 2 ppm & 1.0 to 2.0 \\
3.4 & Building network & 1 & 2 + 2 ppm & 1.0 to 2.0 \\ \hline \hline \end{tabular} (4)  
Comparison of the performance of optimization strategies with changes in total station parameters  
In this test, the results of individual optimization strategies with the changes in the accuracy of the total station (or, rather, the combination of direction/angle and distance measurement accuracies) are evaluated. The horizontal direction and zenith angle measurement accuracies gradually decrease while the accuracy of distance measurement increases, thus gradually reducing the contribution of the angles and increasing the contribution of distance measurements. The accuracy of all three parameters is always changed simultaneously, and the accuracy of both angle measurements is always changed by the same step (20 steps in all). The test parameters are detailed in Table 5.  
\end{table} 
Table 4: Parameters for testing of changes in required accuracies of individual networks.