Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …

Land finance plays a pivotal role and occupies an irreplaceable position in facilitating the
rapid regional integration of China. This study introduced an explanatory framework that …

Traditional time series forecasting methods applied to long time series and multivariate data
often ignore the importance of features and the causal relationships between predictors and …

This study addresses the challenge of modeling temperature-dependent
photoluminescence (PL) in CdS colloidal quantum dots (QD), where PL properties fluctuate …

Accurate and efficient forecasting of regional photovoltaic (PV) power is essential for
enhancing the stability of PV electricity supply and increasing its market share. Recent …

Time granularity is a key parameter necessary for short-time passenger flow prediction of
urban rail transit (URT); however, no universal method is available for its setting. This study …

There is a great need to accurately predict short-term precipitation, which has
socioeconomic effects such as agriculture and disaster prevention. Recently, the forecasting …

Vegetation is a key component of biodiversity and ecosystem stability. The normalized
difference vegetation index (NDVI) is widely used to monitor the vegetation growth status …

This study introduces a novel Convolutional Long Short‐Term Memory neural networks
(ConvLSTM)‐based multi‐site downscaling approach for fire danger prediction, that …

Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …