# Short-Term Electricity-Load Forecasting by deep learning: A comprehensive survey

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/short-term-electricity-load-forecasting-by-deep-learning-a-comprehensive-survey/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Qi Dong,Rubing Huang,Chenhui Cui,Dave Towey,Ling Zhou,Jinyu Tian,Jianzhou Wang |
| Citations | 70 |
| DOI | 10.1016/j.engappai.2025.110980 |
| Fields | Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4410106730 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Rubing Huang](https://scholariq.org/researchers/rubing-huang/)

## Paper journal

- [Engineering Applications of Artificial Intelligence](https://scholariq.org/journals/engineering-applications-of-artificial-intelligence/)

## Paper primary topic

- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)

## Paper topics

- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)
- [Electricity Theft Detection Techniques](https://scholariq.org/topics/electricity-theft-detection-techniques/)
- [Smart Grid and Power Systems](https://scholariq.org/topics/smart-grid-and-power-systems/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.