Industries are generating massive amounts of data due to increased automation and
interconnectedness. As data from various sources becomes more available, the extraction of …

Since the advent of smart agriculture, technological advancements in solar energy have
significantly improved farming practices, resulting in a substantial revival of different crop …

The Internet of Things (IoT) is witnessing a surge in sensor-equipped devices. The data
generated by these IoT devices serve as a critical foundation for informed decision-making …

Resource usage prediction in cloud data centers is critically important. It can improve
providers' service quality and avoid resource wastage and insufficiency. However, the time …

Effective and efficient traffic prediction can provide a reliable data basis for traffic
management in Intelligent Transportation Systems (ITS). While various machine learning …

As part of airport behavior decisions, the accurate prediction of airport delay is highly
significant in optimizing flight takeoff and landing sequences. However, the combination of …

Industry 4.0 is transforming predictive failure management by utilizing deep learning to
enhance maintenance strategies and automate production processes. Traditional methods …

Derived from an effective strategy-direct and multiple-input multiple-output strategy, a
modular neural network based on a bi-level particle swarm optimization algorithm (BLPSO …

The prediction of mobile vehicle demands serves as an effective solution for addressing the
communication resource scarcity caused by the expansion of vehicle-to-Everything (V2X) …

The rapid movement of low Earth orbit (LEO) satellites leads to dynamic changes in their
ground access traffic. Multi-step traffic prediction can sense long-term changes in traffic, and …