The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …

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 …

Solar radiation is one of the cleanest sources of renewable energy, and it affects the carbon
sink functions of terrestrial ecosystems. Although efforts have been made to establish solar …

The accuracy of solar energy forecasting is critical for power system planning, management,
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …

Solar is a significant renewable energy source. Solar energy can provide for the world's
energy needs while minimizing global warming from traditional sources. Forecasting the …

Stock market's volatile and complex nature makes it difficult to predict the market situation.
Deep Learning is capable of simulating and analyzing complex patterns in unstructured …

The conventional multi-step ahead solar radiation prediction method ignores the time-
dependence of a future solar radiation time series. Therefore, according to sequence-to …

Accurate solar radiation forecasting can effectively improve solar energy utilization efficiency
and decrease the operational cost of solar photovoltaic power plants. However, some …

Reliable estimation of solar irradiance is required for many solar energy applications such
as photovoltaics, water heating, cooking, solar microgrids, etc. Deep Learning techniques …

This paper focuses on integrating two popular signal processing techniques, ie, variational
mode decomposition (VMD) and discrete wavelet transform (DWT), with deep learning (DL) …