The emergence of ultra-dense 5G networks and a large number of connected devices will
bring with them significant increases in energy consumption, operating costs, and CO 2 …

The integration of Photovoltaic (PV) power into energy market requires the development of
accurate PV power forecasting models. Apart from the prediction model the selection of the …

A data-driven short-term power generation forecasting model has been proposed to address
the problems of information redundancy and low forecasting accuracy for the previous …

There is an increasing need for capable models in the forecast of the output of solar
photovoltaic panels. These models are vital for optimizing the performance and …

This study aims to utilize deep learning (DL) technology to address the issue of carbon soot
emission in traditional internal combustion engines. Spraying and combustion experiments …

The morphology of the cladding layer is directly affected by the process parameters of laser
cladding. To improve the morphology of single-track cladding layer, it is necessary to …

A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is
proposed in this paper, considering multimodal travel behavior and microscopic traffic …

Recently, renewable energy has been widely deployed. Among all renewable energy
sources, photovoltaic power is widely deployed in the grid. Because of the instability of PV …

In numerous industrial contexts, precise analysis and forecasting of electrical signals within
three-phase systems are indispensable. As a result, this work presents DeepPhase, a hybrid …

The demand for electrical energy is continuously increasing in these days, particularly due
to advancements in the industrial sector. This surge in demand has underscored the …