## 3 Results and Discussion
### Comparisons with BPNN Models
#### 3.1.2 Comparisons of Prediction Results  
From Figures 9 and 10, the worst and the best CNN and BPNN models, respectively, were selected for comparison. The best CNN model, except for CNN-FSPA, was the non-FAIS model with Test 2 parameters and the best BPNN model, except for BPNN-FSPA, was the non-LHES model with Test 3 parameters. The worst CNN model was the non-BMTS model with Test 4 parameters and the worst BPNN model was the non-TAIS model with Test 4 parameters. The prediction results and errors for four earthquakes (M4.5, M5.6, M5.1 and M4.0) at four stations (FAIS, LHES, BMTS and TAIS) are shown in Table 6.  
As shown in Table 6, all the errors of the CNN models were lower than those of the corresponding BPNN models for the same earthquakes. In addition, the worst testing model (non-BMTS) of the CNNs had an error rate of 25.0% and the corresponding non-TAIS model of the BPNNs had an error rate of 81.6%.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Magnitude**} & \multicolumn{3}{c}{**CNN-PSPA**} & \multicolumn{3}{c}{**BPNN-PSPA**} \\ \cline{3-8}  & & **Observed** & **Predicted** & **Error** & **Observed** & **Predicted** & **Error** \\  & & **(FAIS)** & **(FAIS)** & **(LAIS)** & **(LAIS)** & **Error** \\ \hline \multirow{4}{*}{Best testing} & M4.5 & 2.86 & 2.48 & 13.2\% & 2.05 & 2.51 & 18.3\% \\  & M5.6 & 1.89 & 1.98 & 4.7\% & 2.55 & 2.69 & 5.2\% \\  & M5.1 & 1.90 & 1.93 & 1.7\% & 2.80 & 3.04 & 8.3\% \\  & M4.0 & 1.81 & 2.12 & 17.3\% & 3.42 & 2.53 & 26.0\% \\ \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Magnitude**} & **Observed** & **Predicted** & **Error** & **Observed** & **Predicted** & **Error** \\  & & **(BMTs)** & **(BMTs)** & **(TAIS)** & **(TAIS)** & **(TAIS)** & **Error** \\ \hline \multirow{4}{*}{Worst testing} & M4.5 & 2.79 & 1.99 & 28.6\% & 2.34 & 3.85 & 64.4\% \\  & M5.6 & 2.45 & 2.30 & 6.1\% & 3.56 & 7.30 & 104.8\% \\ \cline{1-1}  & M5.1 & 1.78 & 1.77 & 0.7\% & 3.10 & 4.61 & 48.6\% \\ \cline{1-1}  & M4.0 & 2.01 & 1.81 & 9.9\% & 3.65 & 5.33 & 45.9\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparisons of CNNs and BPNNs.  
Figure 10: Errors of BPNN predictions.  
It can also be seen from Table 6 that the error difference between the best and the worst predictions of the CNNs was much lower than for the BPNNs. Comparisons between the best and worst of the CNN-PSPA models showed that the errors of the results did not differ much. Furthermore, the earthquakes with magnitude 5.1 gave the best results, with little fluctuation in this CNN-PSPA. The CNNs showed better stability and less sensitivity to the parameters. In contrast, the difference between the best and worst tests of the BPNNs was significant. The worst of the BPNNs showed both a larger variance and the largest error of 104.8%, appearing in the M5.6 earthquakes. The BPNN-PSPA test for a magnitude of 5.6 showed the difference between the worst test with the largest error rate of 104.8% and the best test with the smallest error rate of 5.2%. It can be seen that the BPNN models were very unstable and were adversely affected by changing the parameters. The CNN models outperformed the corresponding BPNN models in terms of test stability.  
Both the stability and the accuracy analyses showed that the CNNs were significantly better than the BPNNs.