# A Hybrid Model of Conformer and LSTM for Ocean Wave Height Prediction
## 3 Results and Discussion
### Comparison with Other Models  
Table 7 lists the prediction effects of Conformer-LSTM, LSTM, CNN, CNN-LSTM, BiLSTM [30], and TCN [31] at stations 41048, 46047, 41040, and 42020, showing that Conformer-LSTM has better performance.  
This table provides the accuracy obtained using different prediction algorithms at all sites. By observing the table, we find that the Conformer-LSTM model achieves better performance at each site.  
By analyzing and comparing the average accuracy data obtained in Table 8, it can be found that the Conformer-LSTM model shows varying degrees of improvement over other traditional models.  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Station** & **Network** & **MAE** & _RMSE_ & _MAPE (\%)_ & \(\mathbf{R^{2}}\) \\ \hline \multirow{8}{*}{41048} & Conformer-LSTM & 0.12909 & 0.17745 & 5.4335 & 0.95961 \\  & LSTM & 0.15055 & 0.20797 & 7.1349 & 0.94629 \\  & CNN & 0.16022 & 0.22598 & 8.4804 & 0.93658 \\  & CNN-LSTM & 0.13436 & 0.18544 & 5.5754 & 0.9559 \\  & BiLSTM & 0.13959 & 0.18937 & 5.9103 & 0.95401 \\  & TCN & 0.16594 & 0.23518 & 6.8163 & 0.92906 \\ \hline \multirow{8}{*}{46047} & Conformer-LSTM & 0.11975 & 0.13394 & 4.829 & 0.96392 \\  & LSTM & 0.12829 & 0.14713 & 4.9998 & 0.95843 \\  & CNN & 0.13453 & 0.15836 & 5.2322 & 0.95135 \\  & CNN-LSTM & 0.125363 & 0.14936 & 4.9756 & 0.95829 \\  & BiLSTM & 0.134413 & 0.16914 & 4.8314 & 0.95314 \\  & TCN & 0.14719 & 0.1795 & 5.7141 & 0.92668 \\ \hline \multirow{8}{*}{41040} & Conformer-LSTM & 0.08856 & 0.11708 & 4.2548 & 0.95025 \\  & LSTM & 0.09194 & 0.12029 & 4.457 & 0.94748 \\  & CNN & 0.09087 & 0.12977 & 4.3603 & 0.94794 \\  & CNN-LSTM & 0.09481 & 0.13303 & 4.6166 & 0.94507 \\  & BiLSTM & 0.09021 & 0.12931 & 4.307 & 0.94834 \\  & TCN & 0.09051 & 0.12693 & 4.4491 & 0.94752 \\ \hline \multirow{8}{*}{42020} & Conformer-LSTM & 0.09719 & 0.15381 & 5.8291 & 0.97768 \\  & LSTM & 0.11294 & 0.17244 & 6.3098 & 0.96875 \\  & CNN & 0.12118 & 0.19562 & 6.8437 & 0.9657 \\  & CNN-LSTM & 0.10647 & 0.17988 & 6.7574 & 0.96987 \\  & BiLSTM & 0.10418 & 0.18021 & 6.4032 & 0.97389 \\  & TCN & 0.14089 & 0.20168 & 7.2607 & 0.95252 \\ \hline \multirow{8}{*}{42057} & Conformer-LSTM & 0.08045 & 0.12654 & 6.0541 & 0.97452 \\  & LSTM & 0.08873 & 0.13230 & 6.8501 & 0.96520 \\  & CNN & 0.09054 & 0.14565 & 6.5521 & 0.96014 \\  & CNN-LSTM & 0.08245 & 0.12975 & 6.4532 & 0.96745 \\  & BiLSTM & 0.10451 & 0.15325 & 7.2523 & 0.95412 \\  & TCN & 0.09514 & 0.14547 & 6.8514 & 0.96123 \\ \hline \multirow{8}{*}{46025} & Conformer-LSTM & 0.11123 & 0.14576 & 5.4541 & 0.96741 \\  & LSTM & 0.13574 & 0.16345 & 6.2414 & 0.95245 \\ \cline{1-1}  & CNN & 0.14537 & 0.17632 & 6.8544 & 0.94951 \\ \cline{1-1}  & CNN-LSTM & 0.11954 & 0.15016 & 5.8541 & 0.96247 \\ \cline{1-1}  & BiLSTM & 0.13246 & 0.16854 & 6.2484 & 0.95126 \\ \cline{1-1}  & TCN & 0.14767 & 0.19754 & 7.2541 & 0.94254 \\ \hline \multirow{8}{*}{42002} & Conformer-LSTM & 0.09451 & 0.15461 & 6.6554 & 0.96314 \\ \cline{1-1}  & LSTM & 0.10004 & 0.16275 & 7.0541 & 0.95445 \\ \cline{1-1}  & CNN & 0.10547 & 0.16345 & 7.2964 & 0.95521 \\ \cline{1-1}  & CNN-LSTM & 0.09679 & 0.15778 & 6.8471 & 0.95842 \\ \cline{1-1}  & BiLSTM & 0.11047 & 0.16547 & 7.2333 & 0.95124 \\ \cline{1-1}  & TCN & 0.11245 & 0.17571 & 8.5114 & 0.94897 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Evaluation results of different models at different stations.  
In this study, we utilized data from two buoys located in the Gulf of Mexico and two in the Pacific Ocean. While these buoys provided valuable data for our analysis, it is important to note that the limited number of buoys and their close proximity in the Pacific Ocean could constrain the generalizability of our findings. Future studies should consider incorporating data from a larger number of buoys distributed more widely across different oceanic regions to enhance the robustness of the predictions.