Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction

Research article (Applied Energy, 2024) · cited 16× · AI/ML
Press Enter · cited answer in seconds

Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction

Summary

Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction is a scholarly article[1].

Key Facts

  • Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction's instance of is recorded as scholarly article[2].

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction. Retrieved May 24, 2026, from https://4ort.xyz/entity/learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas
MLA “Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas.
BibTeX @misc{4ortxyz_learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction}}, year = {2026}, url = {https://4ort.xyz/entity/learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase space reconstruction — https://4ort.xyz/entity/learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/learning-global-and-local-features-of-power-load-series-through-transformer-and-2d-cnn-an-image-based-multi-step-forecas · Last refreshed: