Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
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) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
How solar radiation forecasting impacts the utilization of solar energy: A critical review
The demand for energy generation from solar energy resource has been exponentially
increasing in recent years. It is integral for a grid operator to maintain the balance between …
increasing in recent years. It is integral for a grid operator to maintain the balance between …
[HTML][HTML] Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China
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 …
of solar energy utilization systems. Existing empirical and machine learning models for …
A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions
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 …
(GBT), multilayer perceptron neural network (MLPNN), two types of adaptive neuro-fuzzy …
Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation
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 …
and reliable alternative source of energy. Where, the output of solar energy systems is highly …
Daily reference evapotranspiration prediction based on hybridized extreme learning machine model with bio-inspired optimization algorithms: Application in …
Reliable and accurate prediction of reference evapotranspiration (ETo) is a precondition for
the efficient management and planning of agricultural water resources as well as the optimal …
the efficient management and planning of agricultural water resources as well as the optimal …
Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India
Solar radiation is a critical requirement for all solar power plants. As it is a time-varying
quantity, the power output of any solar power plant is also time variant in nature. Hence, for …
quantity, the power output of any solar power plant is also time variant in nature. Hence, for …
[HTML][HTML] Improving drought modeling based on new heuristic machine learning methods
Drought modeling is vital for designing and managing water resource systems due to its
significant effects on agriculture and other components of the environment. This study …
significant effects on agriculture and other components of the environment. This study …
Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple …
Real-time energy management systems that are designed to support consumer supply and
demand spectrums of electrical energy continue to face challenges with respect to designing …
demand spectrums of electrical energy continue to face challenges with respect to designing …
Comparison of four heuristic regression techniques in solar radiation modeling: Kriging method vs RSM, MARS and M5 model tree
In this study, four different heuristic regression methods including Kriging, response surface
method (RSM), multivariate adaptive regression (MARS) and M5 model tree (M5Tree) have …
method (RSM), multivariate adaptive regression (MARS) and M5 model tree (M5Tree) have …