Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison

Ü Ağbulut, AE Gürel, Y Biçen - Renewable and Sustainable Energy …, 2021 - Elsevier
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …

An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …

ZM Yaseen, SO Sulaiman, RC Deo, KW Chau - Journal of Hydrology, 2019 - Elsevier
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …

A review on global solar radiation prediction with machine learning models in a comprehensive perspective

Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …

Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy

Z Cai, J Gu, J Luo, Q Zhang, H Chen, Z Pan… - Expert Systems with …, 2019 - Elsevier
Since its introduction, kernel extreme learning machine (KELM) has been widely used in a
number of areas. The parameters in the model have an important influence on the …

Performance analysis of hybrid PV/diesel/battery system using HOMER: A case study Sabah, Malaysia

LM Halabi, S Mekhilef, L Olatomiwa… - Energy conversion and …, 2017 - Elsevier
This study considered two decentralized power stations in Sabah, Malaysia; each contains
different combination of photovoltaic (PV), diesel generators, system converters, and storage …

[HTML][HTML] Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China

J Fan, L Wu, F Zhang, H Cai, W Zeng, X Wang… - … and Sustainable Energy …, 2019 - Elsevier
Accurate estimation of global solar radiation (R s) is essential to the design and assessment
of solar energy utilization systems. Existing empirical and machine learning models for …

Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in …

D Cho, C Yoo, J Im, DH Cha - Earth and Space Science, 2020 - Wiley Online Library
Forecasts of maximum and minimum air temperatures are essential to mitigate the damage
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …

Sizing and forecasting techniques in photovoltaic-wind based hybrid renewable energy system: A review

AK Bansal - Journal of Cleaner Production, 2022 - Elsevier
With increasing awareness towards environmental concern, efforts are made to reduce
harmful effects of conventional electricity generation methods and uses of renewable …

Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia

S Ghimire, RC Deo, NJ Downs, N Raj - Journal of cleaner production, 2019 - Elsevier
To support alternative forms of energy resources, the prediction of global incident solar
radiation (I rad) is critical to establish the efficacy of solar energy resources as a free and …

A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I)

A Rohani, M Taki, M Abdollahpour - Renewable Energy, 2018 - Elsevier
The main objective of this paper is to present Gaussian Process Regression (GPR) as a new
accurate soft computing model to predict daily and monthly solar radiation at Mashhad city …