Although the diagnosis methods of rotating machinery based on convolutional neural
network (CNN) have achieved great success, they generally assume the number of normal …

Recently, numerous new data-driven methods have been proposed. But most of them
focused on the innovation of models and algorithms, and rarely discussed and optimized …

Efforts to develop effective climate strategies necessitate a better understanding of the
relationship between terrestrial water and carbon cycles. Water use efficiency (WUE) has …

Agriculture plays an important role in Senegalese economy and annual early warning
predictions of crop yields are highly relevant in the context of climate change. In this study …

The rapid computerized simulation of stochastic computing (SC) systems is a challenging
problem. A method for agile simulation of SC image processing is proposed in this work. The …

Accurate yield forecasts can assist decision-makers in developing plans to bridge the food
demand gap in the context of changing climatic conditions. Literature shows a variety of …

Accurate short-term precipitation forecast is of social and economic significance for
preventing severe weather damage. Deep learning has been rapidly adopted in nowcasting …

Near-surface projected wind changes in the Caribbean Sea (CAR) related to climate
warming are analyzed using 24 General Circulation Models (GCM) from the CMIP6 …

Realistic estimates of surface wind speed (WS) are an essential prerequisite for process‐
based air–sea interaction studies and numerical modelling needs. In this context, historical …

Rising global sea levels have been touted as the major threat that is going to affect small
islands in the coming years. In this study, potential inundation that can occur in the small …