## 4 Experiments
### Main Results
#### 4.2.2 Univariate Forecasting Results  
As shown in Table 3, the univariate experimental results on two typical datasets are listed. Compared with the experimental results of the baseline models, DESTformer still achieves the best performance in long-term prediction tasks. In particular, when the input length is set to 96 and the prediction length is set to 336, the DESTformer achieves an  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Models**} & \multicolumn{2}{c}{**DESTformer**} & \multicolumn{2}{c}{**FEDformer**[3]} & \multicolumn{2}{c}{**Autoformer**[2]} & \multicolumn{2}{c}{**Informer**[1]} & \multicolumn{2}{c}{**LogTrans**[21]} & \multicolumn{2}{c}{**ARIIMA**[37]} & \multicolumn{2}{c}{**LSTM**[34]} \\ \cline{3-14} \multicolumn{2}{c}{**Metric**} & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** \\ \hline \multirow{5}{*}{**mini**} & 96 & **0.198** & **0.266** & 0.203 & 0.287 & 0.255 & 0.339 & 0.365 & 0.453 & 0.768 & 0.642 & 1.354 & 0.829 & 2.041 & 1.073 \\  & 192 & **0.255** & **0.317** & 0.269 & 0.328 & 0.281 & 0.340 & 0.533 & 0.563 & 0.989 & 0.757 & 1.562 & 0.986 & 2.249 & 1.112 \\  & 336 & **0.311** & **0.358** & 0.325 & 0.366 & 0.339 & 0.372 & 1.363 & 0.887 & 1.334 & 0.872 & 1.842 & 1.212 & 2.568 & 1.238 \\  & 720 & **0.402** & **0.398** & 0.421 & 0.415 & 0.422 & 0.419 & 3.379 & 1.388 & 3.048 & 1.328 & 2.315 & 1.712 & 2.720 & 1.287 \\ \hline \multirow{5}{*}{**mini**} & 96 & **0.187** & **0.296** & 0.193 & 0.308 & 0.201 & 0.317 & 0.274 & 0.368 & 0.258 & 0.357 & 0.252 & 0.362 & 0.375 & 0.437 \\  & 192 & **0.195** & **0.307** & 0.201 & 0.315 & 0.222 & 0.334 & 0.296 & 0.386 & 0.266 & 0.368 & 0.301 & 0.393 & 0.442 & 0.473 \\  & 336 & **0.203** & **0.325** & 0.214 & 0.329 & 0.231 & 0.338 & 0.300 & 0.394 & 0.280 & 0.380 & 0.322 & 0.403 & 0.439 & 0.473 \\  & 720 & **0.229** & **0.338** & 0.246 & 0.355 & 0.254 & 0.361 & 0.373 & 0.439 & 0.283 & 0.376 & 0.377 & 0.462 & 0.980 & 0.814 \\ \hline \multirow{5}{*}{**mini**} & 96 & **0.127** & **0.259** & 0.148 & 0.278 & 0.197 & 0.323 & 0.847 & 0.752 & 0.968 & 0.812 & 1.365 & 0.911 & 1.453 & 1.049 \\  & 192 & **0.155** & **0.355** & 0.271 & 0.380 & 0.300 & 0.369 & 1.204 & 0.895 & 1.040 & 0.851 & 1.235 & 0.953 & 1.846 & 1.179 \\  & 336 & **0.436** & **0.469** & 0.460 & 0.500 & 0.509 & 0.524 & 1.672 & 1.036 & 1.659 & 1.081 & 1.563 & 1.123 & 2.136 & 1.231 \\  & 720 & **0.998** & **0.732** & 1.195 & 0.841 & 1.447 & 0.941 & 2.478 & 1.310 & 1.941 & 1.127 & 1.780 & 1.240 & 2.984 & 1.427 \\ \hline \multirow{5}{*}{**mini**} & 96 & **0.562** & **0.354** & 0.587 & 0.366 & 0.613 & 0.388 & 0.719 & 0.391 & 0.684 & 0.384 & 0.632 & 0.534 & 0.843 & 0.453 \\  & 192 & **0.593** & **0.355** & 0.604 & 0.373 & 0.616 & 0.382 & 0.696 & 0.379 & 0.685 & 0.390 & 0.695 & 0.592 & 0.847 & 0.453 \\  & 336 & **0.603** & **0.377** & 0.621 & 0.383 & 0.622 & 0.337 & 0.777 & 0.420 & 0.733 & 0.408 & 0.732 & 0.620 & 0.853 & 0.455 \\  & 720 & **0.599** & **0.356** & 0.626 & 0.382 & 0.660 & 0.408 & 0.864 & 0.472 & 0.717 & 0.396 & 0.793 & 0.711 & 1.500 & 0.805 \\ \hline \multirow{5}{*}{**mini**} & 96 & **0.202** & **0.276** & 0.217 & 0.296 & 0.266 & 0.336 & 0.300 & 0.384 & 0.458 & 0.490 & 0.423 & 0.446 & 0.369 & 0.406 \\  & 192 & **0.254** & **0.318** & 0.276 & 0.336 & 0.307 & 0.367 & 0.594 & 0.544 & 0.658 & 0.589 & 0.492 & 0.511 & 0.416 & 0.435 \\  & 336 & **0.307** & **0.369** & 0.339 & 0.380 & 0.359 & 0.395 & 0.578 & 0.523 & 0.797 & 0.652 & 0.533 & 0.562 & 0.455 & 0.454 \\  & 720 & **0.395** & **0.417** & 0.403 & 0.428 & 0.419 & 0.428 & 1.059 & 0.741 & 0.869 & 0.675 & 0.591 & 0.612 & 0.535 & 0.520 \\ \hline \multirow{5}{*}{**mini**} & 24 & **3.019** & **1.256** & 3.228 & 1.260 & 3.483 & 1.287 & 5.764 & 1.677 & 4.480 & 1.444 & 4.121 & 1.562 & 5.914 & 1.734 \\  & 36 & **2.418** & **1.069** & 2.679 & 1.080 & 3.103 & 1.148 & 4.755 & 1.467 & 4.799 & 1.467 & 4.992 & 1.588 & 6.631 &MSE reduction of 1.5% on the ETT dataset with obvious periodicity.