The uncertainty associated with modeling and performance prediction of solar photovoltaic
systems could be easily and efficiently solved by artificial intelligence techniques. During the …

Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …

In achieving water resource management goals such as irrigation scheduling, an accurate
estimate of reference evapotranspiration (ET 0) is critical. Support vector regression (SVR) …

Oil production estimation plays a critical role in economic plans for local governments and
organizations. Therefore, many studies applied different Artificial Intelligence (AI) based …

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 …

Reliable knowledge of solar radiation is an essential requirement for designing and
planning solar energy systems. Thus, this paper presents a novel hybrid model for predicting …

Daily observations of meteorological parameters, air temperature, air pressure, relative
humidity, water vapor pressure and sunshine duration hours observed at 12 stations in …

Accurate global solar radiation data are fundamental information for the allocation and
design of solar energy systems. The current study compared different machine learning and …

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 …

Accurate forecasting of renewable energy sources plays a key role in their integration into
the grid. This study proposes machine learning algorithms to predict the hourly solar …