Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …

Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …

Diabetic retinopathy (DR) is a common complication of diabetes mellitus, and retinal blood
vessel damage can lead to vision loss and blindness if not recognized at an early stage …

Solar forecasting from ground-based sky images has shown great promise in reducing the
uncertainty in solar power generation. With more and more sky image datasets available in …

Integrating large proportions of intermittent renewable energy sources into electric grids is
challenging. A well-established approach aimed at addressing this difficulty involves the …

Cloud dynamics are the main factor influencing the intermittent variability of short-term solar
irradiance, and therefore affect the solar farm output. Sky images have been widely used for …

The establishment of composition-microstructure-property relationship is a long-standing
topic in materials science, yet neither continuum mechanics approaches nor machine …

Accurate prediction of photovoltaic power generation is vital to guarantee smooth operation
of power stations and ensure users' electricity consumption. As a good forecasting tool …

Accurate photovoltaic (PV) power generation forecasting is very important for making
economic and reliable power dispatching plans. This study proposes a multi-step ahead PV …

Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the
intermittent nature of solar power. Sky-image-based solar forecasting using deep learning …