A systematic review on predicting PV system parameters using machine learning-Reference-Cited by-同舟云学术

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A systematic review on predicting PV system parameters using machine learning

Published:2023-06 Issue:6 Volume:9 Page:e16815
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Jobayer Md^ORCID,Shaikat Md Al Hasan,Naimur Rashid Md,Hasan Md Rakibul^ORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference72 articles.

1. Gaussian kernel based SVR model for short-term photovoltaic MPP power prediction;Onal;Comput. Syst. Sci. Eng.,2022

2. Solar Ultraviolet Variability over Time Periods of Aeronomic Interest;Woods,2002

3. Accurate solar cell modeling via genetic neural network-based meta-heuristic algorithms;Wang;Front. Energy Res.,2021

4. Photovoltaic cell parameter estimation based on improved equilibrium optimizer algorithm;Wang;Energy Convers. Manag.,2021

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3. Research on a novel photovoltaic power forecasting model based on parallel long and short-term time series network;Energy;2024-04

4. Effect of Saharan dust episodes on the accuracy of photovoltaic energy production forecast in Hungary (Central Europe);Renewable and Sustainable Energy Reviews;2024-04

5. Detection and analysis of deteriorated areas in solar PV modules using unsupervised sensing algorithms and 3D augmented reality;Heliyon;2024-03

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