In recent years, machine learning, especially various deep neural networks, as an emerging
technique for data analysis and processing, has brought novel insights into the development …

Internal combustion engine vehicles, although conventionally playing essential roles in
seaport logistic operation, are major sources of carbon emissions. To guarantee the “green …

The sixth generation (6G) wireless communication network presents itself as a promising
technique that can be utilized to provide a fully data-driven network evaluating and …

One of the most challenging tasks for clinicians is detecting symptoms of cardiovascular
disease as earlier as possible. Many individuals worldwide die each year from …

Wind-driven turbines utilizing the doubly-fed induction generators aligned with the
progressed IEC 61400 series standards have engrossed specific consideration as of their …

Hybrid cloud computing enables enterprises to get the best of both private and public cloud
models. One of its primary benefits is to reduce operational costs, and the prerequisite is that …

This proof-of-concept study provides a novel method for robust-stable scheduling in dynamic
flow shops based on deep reinforcement learning (DRL) implemented with OpenAI …

To benefit from the advantages of Reinforcement Learning (RL) in industrial control
applications, RL methods can be used for optimal tuning of the classical controllers based …

In the near future, microgrids will become more prevalent as they play a critical role in
integrating distributed renewable energy resources into the main grid. Nevertheless …

Ultra-reliable and Low-latency Communications (URLLC) is expected to be one of the most
critical characteristics Beyond fifth-Generation (B5G) cellular networks with stringent low …