---
title: "robikscube/hourly-energy-consumption: papers citing it"
description: "3 papers in the tracked journals link to the Kaggle dataset robikscube/hourly-energy-consumption in their Crossref records, the first in 2022; most of them (1) in 2026."
url: https://scholar4ai.com/code/kaggle-robikscube-hourly-energy-consumption
markdown_url: https://scholar4ai.com/code/kaggle-robikscube-hourly-energy-consumption.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the Kaggle dataset robikscube/hourly-energy-consumption in their Crossref records, the first in 2022; most of them (1) in 2026. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# robikscube/hourly-energy-consumption: papers linking to it

Research papers in the 480 tracked journals that link to robikscube/hourly-energy-consumption (https://www.kaggle.com/datasets/robikscube/hourly-energy-consumption), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- Kaggle
- https://www.kaggle.com/datasets/robikscube/hourly-energy-consumption

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the Kaggle dataset robikscube/hourly-energy-consumption in their Crossref records, the first in 2022; most of them (1) in 2026.
- By category: AI (2) and Operations Research (1); the journals with the most are Expert Systems with Applications (1), Neural Computing and Applications (1) and Mathematical Programming Computation (1).

## By year

*Papers linking to robikscube/hourly-energy-consumption by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2025 | 1 |
| 2026 | 1 |

## Journals

*Journals whose papers link to robikscube/hourly-energy-consumption most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Mathematical Programming Computation](https://scholar4ai.com/journals/mathematical-programming-computation.md) | 1 |

## Papers

*Papers linking to robikscube/hourly-energy-consumption, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-10-19 | [A dynamic programming approach for generalized nearly isotonic optimization](https://doi.org/10.1007/s12532-022-00229-x) | [Mathematical Programming Computation](https://scholar4ai.com/journals/mathematical-programming-computation.md) | Zhensheng Yu, Xuyu Chen, Xudong Li | 7 | cites it |
| 2025-12-09 | [EnergyFormer: dual-supervised adaptive multi-scale Transformer for multistep energy forecasting](https://doi.org/10.1016/j.eswa.2025.130750) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Xiaorui Shao, Ruizhang Huang, Yongbin Qin | 3 | cites it |
| 2026-07-01 | [Hybrid machine learning approach for short-term load forecasting in smart grids](https://doi.org/10.1007/s00521-026-12295-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Amnah Alhussain, S. M. Suhail Hussain | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). robikscube/hourly-energy-consumption: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-robikscube-hourly-energy-consumption

```bibtex
@misc{scholar4ai-code-kaggle-robikscube-hourly-energy-consumption,
  author = {{Scholar4AI}},
  title = {robikscube/hourly-energy-consumption: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-robikscube-hourly-energy-consumption}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).