Time Series Forecasting On Etth1 192 1
المقاييس
MAE
MSE
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | MAE | MSE |
|---|---|---|
| time-evidence-fusion-network-multi-source | 0.419 | 0.433 |
| segrnn-segment-recurrent-neural-network-for | 0.402 | 0.385 |
| ltboost-boosted-hybrids-of-ensemble-linear | 0.406 | 0.396 |
| disentangled-interpretable-representation-for | - | 0.407 |
| long-term-forecasting-with-tide-time-series | 0.422 | 0.412 |
| xpatch-dual-stream-time-series-forecasting | 0.395 | 0.376 |
| learning-structured-components-towards | 0.398 | 0.379 |
| mixture-of-linear-experts-for-long-term-time | - | 0.453 |
| mixture-of-linear-experts-for-long-term-time | - | 0.403 |
| are-transformers-effective-for-time-series | 0.416 | 0.405 |
| a-time-series-is-worth-64-words-long-term | 0.429 | 0.413 |
| film-frequency-improved-legendre-memory-model | 0.423 | 0.414 |
| prformer-pyramidal-recurrent-transformer-for | - | 0.397 |
| patchmixer-a-patch-mixing-architecture-for | 0.394 | 0.373 |
| revisiting-long-term-time-series-forecasting | 0.412 | 0.404 |
| are-transformers-effective-for-time-series | 0.415 | 0.408 |
| tsmixer-lightweight-mlp-mixer-model-for | 0.418 | 0.399 |