Manuscript Topics

Prospectus societies consume large amounts of fossil fuel annually, which provides a significant demand worldwide for the energy transition. Therefore, the rapid transformation of this supplementary fuel to remove the increasing concerns of CO2 emissions has played a vital role in environmental challenges. Meanwhile, large datasets have been generated from industrial units, experimental setups, and even numerical models, primarily unexploited. These large datasets remain to be analyzed, understood, and used for modeling and optimization at various levels of the upstream and downstream industries variations.

On the other hand, artificial intelligence, including perception, neural networks, machine learning, and knowledge representation, has been driving revolutions in diverse areas, such as autonomous vehicles, robotic manipulators, image analysis, computer vision, art creation, natural language processing, time-series analysis, and target online advertisement. This has made Artificial Intelligence algorithms/methods a promising tool for modeling and optimizing chemical processes.

Topics to be involved

This special issue aims to publish selective novel ongoing research contributions towards new algorithms and techniques in applying artificial intelligence methods to the energy transition and how to develop valuable toolboxes to eliminate the environmental issues. Potential topics may include, but are not limited to:

• Innovative modeling approaches integrating first principles and Artificial Intelligence    
• Hybrid modeling and multiple-objective optimization    
• Predict essential keys in the Industry by Artificial Intelligence    
• Deep learning approaches in modeling and diagnosis    
• Data-driven modeling, optimization, and decision making    
• Environmental pollution reduction using Artificial Intelligence    
• Predict essential keys in the Environmental by Artificial Intelligence    
• Pollutant monitoring and tracing using Artificial Intelligence    
• Digitalization, visualization, and interpretation of Energy processes and virtual process manufacturing    
• Smart optimal design, operation, and control using Artificial Intelligence.

Instruction for Authors
http://www.aimspress.com/aimsgeo/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/