# Research on Transmission Task Static Allocation Based on Intelligence Algorithm
## 4 Experiments
### Algorithm Experiments
In all tests of the three parameter groups, the highest value is completely consistent. In this case, it can be considered that the evaluation value calculated according to the three groups of parameters of the algorithm is the global optimal solution. Experiment 2: the objective is to verify the effectiveness of the algorithm through the success rate. In combination with the results of Experiment 1, three groups of DPSO result data are taken as the global optimal solution and recalculated, and the proportion of the global optimal solution can then be calculated by other algorithms to verify the effectiveness of the algorithm. The algorithm is compared and the best group of algorithm parameters selected from Experiment 1. The obtained experimental data are shown in Table 7. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm and Parameter**} & \multicolumn{6}{c}{**Number of Equipment Items and Tasks**} \\ \cline{2-7}  & **20** & **21** & **22** & **23** & **24** & **25** \\ \hline DPSO (0.3,0.2,0.5) & 0.942249 & 0.940732 & 0.941009 & 0.948124 & 0.936484 & 0.945267 \\ \hline DPSO (0.1,0.2,0.7) & 0.942242 & 0.940732 & 0.941009 & 0.948129 & 0.936482 & 0.945276 \\ \hline DPSO (0.5,0.1,0.4) & 0.942251 & 0.940732 & 0.941009 & 0.948129 & 0.936485 & 0.945276 \\ \hline DPSO (0.4,0.1,0.5) & 0.942251 & 0.940732 & 0.941009 & 0.948129 & 0.936485 & 0.945276 \\ \hline DPSO (0.3,0.1,0.6) & 0.942251 & 0.940732 & 0.941009 & 0.948129 & 0.936485 & 0.945276 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._  
Figure 5: Comparison chart of multi-algorithm comprehensive evaluation average. Analysis of experimental data:  
1. Except for DPSO, the success rate of all algorithms decreases gradually with the number of tasks. 2. Compared with other algorithms, the GA calculation results are the worst. The IGA, PSO-GA, and GA-PSO calculation results are equivalent, but with the increase in the number of tasks, the gap between the GA and DPSO calculation results is wide. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm and Parameter**} & \multicolumn{8}{c}{**Number of Equipment Items and Tasks**} \\ \cline{2-10}  & **8** & **9** & **10** & **11** & **12** & **13** & **14** & **15** & **16** \\ \hline GA (0.6,0.4) & 100\% & 100\% & 99\% & 97\% & 89\% & 97\% & 90\% & 81\% & 77\% \\ \hline IGA (0.8,0.1,0.1) & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 99\% & 100\% \\ \hline IGA (0.6,0.2,0.2) & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% \\ \hline PSO-GA (0.6) & 99\% & 99\% & 97\% & 95\% & 92\% & 93\% & 88\% & 91\% & 81\% \\ \hline GA-PSO (0.3,0.1,0.6) & 100\% & 100\% & 100\% & 100\% & 98\% & 100\% & 97\% & 99\% & 94\% \\ \hline GA-PSO (0.6,0.2,0.2) & 100\% & 100\% & 100\% & 98\% & 100\% & 99\% & 96\% & 96\% & 94\% \\ \hline DPSO & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% \\ \hline \multicolumn{10}{c}{**Number of Equipment Items and Tasks**} \\ \cline{2-10}  & **17** & **18** & **19** & **20** & **21** & **22** & **23** & **24** & **25** \\ \hline GA (0.6,0.4) & 48\% & 46\% & 55\% & 58\% & 21\% & 12\% & 18\% & 10\% & 7\% \\ \hline IGA (0.8,0.1,0.1) & 97\% & 96\% & 98\% & 100\% & 99\% & 89\% & 98\% & 96\% & 87\% \\ \hline IGA (0.6,0.2,0.2) & 99\% & 95\% & 96\% & 100\% & 98\% & 86\% & 97\% & 93\% & 77\% \\ \hline PSO-GA (0.6) & 84\% & 86\% & 75\% & 84\% & 78\% & 71\% & 82\% & 79\% & 69\% \\ \hline GA-PSO (0.3,0.1,0.6) & 94\% & 87\% & 84\% & 91\% & 93\% & 84\% & 84\% & 83\% & 72\% \\ \hline GA-PSO (0.6,0.2,0.2) & 97\% & 91\% & 89\% & 90\% & 86\% & 84\% & 90\% & 86\% & 80\% \\ \hline DPSO & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Multi-algorithm success rate comparison table. Figure 6: Comparison chart of multi-algorithm success rate. It shows that the ICO can effectively improve the calculation success rate of the intelligent algorithm.