Spectrum prediction is a promising technique for improving spectrum exploitation in
cognitive radio networks (CRNs). Accurate spectrum prediction can assist in reducing the …

Radio spectrum prediction is an important task for dynamic spectrum management and
spectrum congestion mitigation. However, due to the complexity and spatiotemporal …

The long-term prediction of deformation in concrete dams is a critical requirement for
maintaining their structural integrity over time in practical management scenarios. While …

Removing raindrops adhering to lenses or glass is challenging since raindrops have more
complex internal structures and optical effects than rain streaks. Existing raindrop removal …

When using point-by-point data input with former series models for wind power prediction,
the prediction accuracy decreases due to data distribution shifts and the inability to extract …

Cognitive radio (CR) is an emerging wireless technology designed to optimize frequency
band usage and address spectrum shortages. Spectrum sensing and prediction are crucial …

Human core and skin temperature (Tcr and Tsk) are crucial indicators of human health and
are commonly utilized in diagnosing various types of diseases. This study presents a deep …

In this paper, we propose a deep learning (DL)-based task-driven spectrum prediction
framework, named DeepSPred. The DeepSPred comprises a feature encoder and a task …

The marine meteorological sensor network (MMSN) is capable of monitoring large-scale
meteorological elements through the joint networking of multiple sensors, which is the …

The rapid advancement in wireless communication technology has led to a high demand for
spectrum resources, causing a scarcity of available spectrum. However, current spectrum …