Energy conservation is the primary task in Wireless Sensor Networks (WSNs) as these tiny
sensor nodes are the backbone of today's Internet of Things (IoT) applications. These nodes …

As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …

With the emerging electric vehicle (EV) and fast charging technologies, EV load forecasting
has become a concern for planners and operators of EV charging stations (CSs). Due to the …

This study proposes a hybrid deep learning approach for dynamic attitude and position
prediction of the tunnel boring machine (TBM) with high accuracy. By utilizing the key …

Protein-protein interactions are of great significance for human to understand the functional
mechanisms of proteins. With the rapid development of high-throughput genomic …

Due to the high availability of large-scale annotated image datasets, paramount progress
has been made in deep convolutional neural networks (CNNs) for image classification tasks …

Reliable and accurate regional multistep-ahead flood forecasts during extreme events are
crucial and beneficial to flood disaster management and preparedness. Hydrologic …

Workload prediction plays a vital role in intelligent resource scaling and load balancing that
maximize the economic growth of cloud service providers as well as users' quality of …

Anomaly detection in time series is an important task to many applications, eg, the
maintenance policies of rotating machines within industries strongly rely on time series …

In many fields, spatiotemporal prediction is gaining more and more attention, eg, air
pollution, weather forecasting, and traffic forecasting. Water quality prediction is a …