Solar radiation is free, and very useful input for most sectors such as heat, health, tourism,
agriculture, and energy production, and it plays a critical role in the sustainability of …

Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …

In the last few years, methods falling within the family of randomization-based machine
learning models have grasped a great interest in the Artificial Intelligence community, mainly …

This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …

This paper presents the application of Particle Swarm Optimization (PSO) Algorithm, Artificial
Neural Networks (ANNs) and Bagged Tree (BT) methods for forecasting seasonal solar …

Solar energy-based technologies have developed rapidly in recent years, however, the
inability to appropriately estimate solar energy resources is still a major drawback for these …

Medium Neural Networks (MNN), Whale Optimization Algorithm (WAO), and Support Vector
Machine (SVM) methods are frequently used in the literature for estimating electricity …

Wind power is a vital power grid component, and wind power forecasting represents a
challenging task. In this study, a series of multiobjective predictive models were created …

This study investigates the impact of cooling methods on the electrical efficiency of
photovoltaic panels (PVs). The efficiency of four cooling techniques is experimentally …

Solar energy is one of the renewable and clean energy sources. Accurate solar radiation
(SR) estimates are therefore needed in solar energy applications. Firstly, two deep learning …