Prediction of Global Horizontal Irradiance Using an Explainable Data Driven Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Prediction of Global Horizontal Irradiance Using an Explainable Data Driven Machine Learning Algorithms

Published:2024-02-06 Issue: Volume: Page:1-18
ISSN:1532-5008
Container-title:Electric Power Components and Systems
language:en
Short-container-title:Electric Power Components and Systems

Author:

Gupta Rahul¹,Yadav Anil Kumar²^ORCID,Jha Shyama Kant³

Affiliation:

1. Department of Electrical Engineering, Netaji Subhas University of Technology, Dwarka, New Delhi, India

2. Department of Instrumentation & Control Engineering, Dr. B. R. Ambedkar National Institute of Technology Jalandhar, Punjab, India

3. Department of Instrumentation & Control Engineering, Netaji Subhas University of Technology, Dwarka, New Delhi, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15325008.2024.2310771

Reference44 articles.

1. Long term estimation of global horizontal irradiance using machine learning algorithms

2. Estimation of mean monthly solar global radiation as a function of temperature

3. The importance of maximum air temperature in the parameterisation of solar radiation in Nigeria

4. Time Series Forecasting of Solar Power Generation Using Facebook Prophet and XG Boost

5. A method for the determination of the global solar radiation from meteorological satellite data

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Harnessing the power of hybrid deep learning algorithm for the estimation of global horizontal irradiance;Science of The Total Environment;2024-09

2. Robust estimation of global horizontal irradiance with modified fuzzy regression functions with a noise cluster in Australia;Energy Conversion and Management: X;2024-07

3. An Efficient and Interpretable Stacked Model for Wind Speed Estimation Based on Ensemble Learning Algorithms;Energy Technology;2024-04-24

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