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 …

A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models

KS Garud, S Jayaraj, MY Lee - International Journal of Energy …, 2021‏ - Wiley Online Library
The uncertainty associated with modeling and performance prediction of solar photovoltaic
systems could be easily and efficiently solved by artificial intelligence techniques. During the …

Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms

FE Jalal, Y Xu, M Iqbal, B Jamhiri, MF Javed - Transportation Geotechnics, 2021‏ - Elsevier
In this study, gene expression programming (GEP) and multi gene expression programming
(MEP) are utilized to formulate new prediction models for determining the compaction …

[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 …

Applications of fuzzy logic in renewable energy systems–a review

L Suganthi, S Iniyan, AA Samuel - Renewable and sustainable energy …, 2015‏ - Elsevier
In recent years, with the advent of globalization, the world is witnessing a steep rise in its
energy consumption. The world is transforming itself into an industrial and knowledge …

A critical review of the models used to estimate solar radiation

J Zhang, L Zhao, S Deng, W Xu, Y Zhang - Renewable and Sustainable …, 2017‏ - Elsevier
Solar radiation data is critical to the design and operation of solar energy utilization systems,
so a large number of models have been proposed and developed to estimate solar radiation …

A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions

M Alizamir, S Kim, O Kisi, M Zounemat-Kermani - Energy, 2020‏ - Elsevier
In this study, the potential of six different machine learning models, gradient boosting tree
(GBT), multilayer perceptron neural network (MLPNN), two types of adaptive neuro-fuzzy …

New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms

MA Khan, F Aslam, MF Javed, H Alabduljabbar… - Journal of Cleaner …, 2022‏ - Elsevier
Bio-composites have become the prime material selection for green concrete because of the
increasing awareness of environmental issues. Due to their highly heterogenous nature …

Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation

LM Halabi, S Mekhilef, M Hossain - Applied energy, 2018‏ - Elsevier
Solar energy plays a vital role in the field of sustainable energy by providing clean, efficient
and reliable alternative source of energy. Where, the output of solar energy systems is highly …

Genetic programming in water resources engineering: A state-of-the-art review

AD Mehr, V Nourani, E Kahya, B Hrnjica, AMA Sattar… - Journal of …, 2018‏ - Elsevier
The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for
automatic generation of computer programs. In recent decades, GP has been frequently …