Multi-site solar power forecasting using gradient boosted regression trees

By C. Persson, P. Bacher, Shiga Takahiro, Henrik Madsen. 2017

360 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/76570af91938c4e68478fb55381c3824ea6b4fb8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Muhammad Naveed Akhter
2. Hazlie Mokhlis
3. Noraisyah Mohamed Shah
4. Saad Mekhilef

In Renewable Energy, Sustainability and the Environment

1. Muhammad Naveed Akhter
2. Hazlie Mokhlis
3. Noraisyah Mohamed Shah
4. Saad Mekhilef
5. Yousef A. Mahmoud
6. Ehab F. El-Saadany
7. Mohamed A. Abdelwahed
8. Zengshi Chen

Citations in the corpus

• Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques (2019, methodology): “Boosting and bagging phenomena are used to enhance the performance of classical regression trees [22, 67].”