# Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data
## 5 Results and Discussion
The table is sorted in descending order according to the mean PC value. The PDN algorithm had the highest mean PC value with 61.2%. In contrast, the LNR algorithm had the worst mean PC value with 48.4%. This was comparable to the maximal and minimal values, where the PDN algorithm had the highest values and the LNR algorithm also had the lowest PC values. Furthermore, the PDN algorithm showed the smallest standard deviation; hence, this algorithm was the most insensitive to the mean PC value. The PDN algorithm had the highest mean PC value with 61.2%. In contrast, the LNR algorithm had the worst mean PC value with 48.4%. This was comparable to the maximal and minimal values, where the PDN algorithm had the highest values and the LNR algorithm also had the lowest PC values. Furthermore, the PDN algorithm showed the smallest standard deviation; hence, this algorithm was the most insensitive to the mean PC value. The PDN algorithm had the highest mean PC value with 61.2%. In contrast, the LNR algorithm had the worst mean PC value with 48.4%. This was comparable to the maximal and minimal values, where the PDN algorithm had the highest values and the LNR algorithm also had the lowest PC values. Furthermore, the PDN algorithm showed the smallest standard deviation; hence, this algorithm was the most insensitive to the mean PC value. The PDN algorithm had the highest mean PC value with 61.2%. In contrast, the LNR algorithm had the worst mean PC value with 48.4%. This was comparable to the maximal and minimal values, where the PDN algorithm had the highest values and the LNR algorithm also had the lowest PC values. Furthermore, the PDN algorithm showed the smallest standard deviation; hence, this algorithm was the most insensitive to the mean PC value. Figure 6: Heat map of the summarized PC values for all events for each algorithm (green—max PC value, red—min PC value; coloring for each heat map separately). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**\#**} & \multirow{2}{*}{**Algorithm**} & \multirow{2}{*}{**Mean**} & \multicolumn{2}{c}{**Standard**} & \multirow{2}{*}{**Max PC**} & \multirow{2}{*}{**Min PC**} & \multicolumn{2}{c}{**Overall Best**} \\  & & & & **Deviation** & & & **[T1, T2]** \\ \hline
3 & PDN & 61.2 & 4.0 & 70.6 & 51.8 & \([-30,110]\) \\
9 & BCP & 60.5 & 5.7 & 77.3 & 46.3 & \([-100,30]\) \\
7 & KCP & 55.8 & 6.0 & 66.9 & 33.3 & \([-40,30]\) \\
8 & CPD & 54.5 & 8.8 & 71.3 & 31.0 & \([-100,20]\) \\
6 & KSS & 53.7 & 6.1 & 71.6 & 39.8 & \([-20,20]\) \\
1 & MAN & 53.3 & 5.0 & 66.7 & 36.7 & \([-90,30]\) \\
5 & MLR & 51.5 & 5.4 & 68.0 & 39.6 & \([-50,40]\) \\
2 & DFN & 48.6 & 6.1 & 60.1 & 33.4 & \([-60,120]\) \\
4 & LNR & 48.4 & 6.3 & 60.9 & 31.5 & \([-30,120]\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Mean and standard deviation, max and min PC, from heat map and overall best time frames. change in the time frame compared to the other algorithms. To this end, CPD was the most affected by a change in the evaluation time frame. The overall best evaluation time frame for each algorithm was the one belonging to the maximal PC value in the summarized heat map. In the case of the BCP algorithm, it was \([T1,\ T2]=[-100,\ 30]\). When calculating the mean time value, shown in Table 3, it resulted in a different evaluation time frame \([T1,\ T2]=[-69,\ 53]\). However, this selection led to worse results. Table 5 indicates that each algorithm benefitted from an individual best overall evaluation time frame [71, 72]. This is an important result for practical application because it illustrated which algorithm should be applied in which individual best overall time frame. Within this evaluation time frame, the algorithm was applied, and the pressure data were evaluated. After determining the overall best time frames, each algorithm was applied with its time frame to all 22 real events. The results are shown in Table 6.  
The table represents the nine algorithms for the 22 real events. Each algorithm was applied in its own overall best evaluation time frame \([T1,\ T2]\).