# Prediction of home energy consumption based on gradient boosting regression tree

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/prediction-of-home-energy-consumption-based-on-gradient-boosting-regression-tree/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Peng Nie,Michèle Roccotelli,Maria Pia Fanti,Zhengfeng Ming,Zhiwu Li |
| Citations | 202 |
| DOI | 10.1016/j.egyr.2021.02.006 |
| Fields | Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.sciencedirect.com/science/article/pii/S2352484721001049/pdf |
| OpenAlex ID | https://openalex.org/W3136570575 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Maria Pia Fanti](https://scholariq.org/researchers/maria-pia-fanti/)

## 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/)
- [Traffic Prediction and Management Techniques](https://scholariq.org/topics/traffic-prediction-and-management-techniques/)
- [Building Energy and Comfort Optimization](https://scholariq.org/topics/building-energy-and-comfort-optimization/)

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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.