## 4 Experiments
### Ablation Studies
#### 4.3.1 Traditional Time Series Decomposition vs. Frequency Decomposition
Therefore, it is believed that the  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{\multirow{2}{*}{**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}{**ARIMA [37]**} & \multicolumn{2}{c}{**LSTM [34]**} \\ \cline{3-14} \multicolumn{1}{c}{**Metric**} & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** & **MSE** & **MAE** \\ \hline \multirow{4}{*}{**FEDformer**} & 96 & **0.058** & **0.177** & 0.072 & 0.206 & 0.065 & 0.189 & 0.080 & 0.217 & 0.075 & 0.208 & 0.211 & 0.362 & 1.921 & 0.963 \\  & 192 & **0.096** & **0.234** & 0.102 & 0.245 & 0.118 & 0.256 & 0.112 & 0.259 & 0.129 & 0.275 & 0.261 & 0.406 & 2.122 & 1.007 \\  & 336 & **0.127** & **0.258** & 0.130 & 0.279 & 0.154 & 0.305 & 0.166 & 0.314 & 0.154 & 0.302 & 0.317 & 0.448 & 2.448 & 1.146 \\  & 720 & **0.154** & **0.317** & 0.178 & 0.325 & 0.182 & 0.335 & 0.228 & 0.380 & 0.160 & 0.366 & 0.487 & 0.334 & 2.554 & 1.120 \\ \hline \multirow{4}{*}{**FEDformer**} & 96 & **0.244** & **0.356** & 0.253 & 0.370 & 0.341 & 0.438 & 0.258 & 0.367 & 0.288 & 0.393 & 0.367 & 0.391 & 0.382 & 0.446 \\  & 192 & **0.264** & **0.354** & 0.282 & 0.386 & 0.345 & 0.428 & 0.285 & 0.388 & 0.432 & 0.483 & 0.423 & 0.446 & 0.410 & 0.463 \\  & 336 & **0.337** & **0.429** & 0.346 & 0.431 & 0.406 & 0.470 & 0.336 & 0.423 & 0.430 & 0.483 & 0.401 & 0.422 & 0.437 & 0.495 \\  & 720 & **0.419** & **0.479** & 0.422 & 0.484 & 0.565 & 0.581 & 0.607 & 0.599 & 0.491 & 0.531 & 0.533 & 0.576 & 0.884 & 0.756 \\ \hline \multirow{4}{*}{**FEDformer**} & 96 & **0.117** & **0.274** & 0.154 & 0.304 & 0.241 & 0.387 & 1.327 & 0.944 & 0.237 & 0.377 & 0.118 & 0.285 & 1.563 & 0.995 \\  & 192 & **0.257** & **0.381** & 0.286 & 0.420 & 0.300 & 0.369 & 1.258 & 0.924 & 0.738 & 0.619 & 0.304 & 0.404 & 1.754 & 1.008 \\  & 336 & **0.497** & **0.450** & 0.511 & 0.555 & 0.509 & 0.524 & 2.179 & 1.296 & 2.018 & 1.070 & 0.736 & 0.598 & 2.035 & 1.003 \\  & 720 & **1.229** & **0.862** & 1.301 & 0.879 & 1.260 & 0.867 & 1.280 & 0.953 & 2.405 & 1.175 & 1.871 & 0.935 & 2.785 & 1.023 \\ \hline \multirow{4}{*}{**FEDformer**} & 96 & **0.198** & **0.298** & 0.207 & 0.312 & 0.246 & 0.346 & 0.257 & 0.353 & 0.226 & 0.317 & 0.422 & 0.435 & 0.756 & 0.369 \\  & 192 & **0.193** & **0.307** & 0.205 & 0.312 & 0.266 & 0.370 & 0.299 & 0.376 & 0.314 & 0.408 & 0.466 & 0.472 & 0.856 & 0.358 \\  & 336 & **0.215** & **0.319** & 0.219 & 0.323 & 0.263 & 0.371 & 0.312 & 0.387 & 0.387 & 0.453 & 0.562 & 0.518 & 0.779 & 0.430 \\  & 720 & **0.230** & **0.300** & 0.244 & 0.344 & 0.269 & 0.372 & 0.366 & 0.436 & 0.437 & 0.491 & 0.634 & 0.590 & 0.458 & 0.750 \\ \hline \multirow{4}{*}{**FEDformer**} & 96 & **0.006** & **0.059** & 0.006 & 0.062 & 0.011 & 0.081 & 0.004 & 0.044 & 0.005 & 0.052 & 0.126 & 0.149 & 0.360 & 0.395 \\  & 192 & **0.005** & **0.058** & 0.006 & 0.062 & 0.008 & 0.067 & 0.002 & 0.040 & 0.006 & 0.060 & 0.188 & 0.212 & 0.452 & 0.421 \\  & 336 & **0.004** & **0.045** & 0.004 & 0.050 & 0.006 & 0.062 & 0.004 & 0.049 & 0.006 & 0.054 & 0.237 & 0.271 & 0.367 & 0.426 \\  & 720 & **0.006** & **0.053** & 0.006 & 0.059 & 0.009 & 0.070 & 0.003 & 0.042 & 0.007 & 0.059 & 0.312 & 0.351 & 0.522 & 0.503 \\ \hline \multirow{4}{*}{**FEDformer**} & 24 & **0.629** & **0.596** & 0.708 & 0.627 & 0.948 & 0.732 & 5.282 & 2.050 & 3.607 & 1.662 & 3.442 & 1.612 & 4.886 & 1.652 \\  & 36 & **0.572** & **0.601** & 0.584 & 0.617 & 0.634 & 0.650 & 4.554 & 1.916 & 2.407 & 1.363 & 3.634 & 1.920 & 5.426 & 1.698 \\ \cline{1-1}  & 48 & **0.702** & **0.652** & 0.717 & 0.697 & 0.791 & 0.752 & 4.  
frequency domain decomposition technique can capture more spatiotemporal information in the frequency domain dimension of sequence data for downstream models to learn.