A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment

MU Mehmood, D Chun, H Han, G Jeon, K Chen - Energy and buildings, 2019 - Elsevier
After decades of evolution and improvements, Artificial Intelligence (AI) is now taking root in
our daily lives, and is starting to profoundly influence the fields of architecture and …

Advances in solar photovoltaic tracking systems: A review

ALR Nadia, NAM Isa, MKM Desa - Renewable and sustainable energy …, 2018 - Elsevier
Solar photovoltaic technology is one of the most important resources of renewable energy.
However, the current solar photovoltaic systems have significant drawbacks, such as high …

Solar radiation prediction using Artificial Neural Network techniques: A review

AK Yadav, SS Chandel - Renewable and sustainable energy reviews, 2014 - Elsevier
Solar radiation data plays an important role in solar energy research. These data are not
available for location of interest due to absence of a meteorological station. Therefore, the …

Ensemble methods for wind and solar power forecasting—A state-of-the-art review

Y Ren, PN Suganthan, N Srikanth - Renewable and Sustainable Energy …, 2015 - Elsevier
This paper reviews state-of-the-art on wind speed/power forecasting and solar irradiance
forecasting with ensemble methods. The ensemble forecasting methods are grouped into …

A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

A Mellit, AM Pavan - Solar energy, 2010 - Elsevier
Forecasting of solar irradiance is in general significant for planning the operations of power
plants which convert renewable energies into electricity. In particular, the possibility to …

Artificial intelligence techniques for photovoltaic applications: A review

A Mellit, SA Kalogirou - Progress in energy and combustion science, 2008 - Elsevier
Artificial intelligence (AI) techniques are becoming useful as alternate approaches to
conventional techniques or as components of integrated systems. They have been used to …

[HTML][HTML] Floating photovoltaic site selection using fuzzy rough numbers based LAAW and RAFSI model

M Deveci, D Pamucar, E Oguz - Applied Energy, 2022 - Elsevier
This study presents a quantitative methodology for Floating Photovoltaic (FPV) power plant
site selection in Turkey using Geographical Information Systems (GIS) and fuzzy sets, which …

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 …

Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models

AK Yadav, H Malik, SS Chandel - Renewable and Sustainable Energy …, 2014 - Elsevier
The prediction of solar radiation is important for several applications in renewable energy
research. Solar radiation is predicted by a number of solar radiation models both …

Predicting solar radiation in the urban area: A data-driven analysis for sustainable city planning using artificial neural networking

AA Tehrani, O Veisi, BV Fakhr, D Du - Sustainable Cities and Society, 2024 - Elsevier
Predicting solar radiation in cities using the Artificial Neural Network model (ANN) is a
pioneering step in transforming future-oriented city planning using solar energy. This …