Recent Advances of Artificial Intelligence in Industrial-based problems: Application of Novel Computation Methods

 

For the last decade, a rising research trend has been covering the evolution of environmental and energy awareness in light of the requirements imposed by the main climate change consensus. Accordingly, a variety of strict rules have been laid down on different industries operating in both the manufacturing and service sectors. Based on these requirements, supply systems have been affected by sustainability issues, the impact of environmental management strategies, and the new opportunities provided to sustainable systems in terms of energy and environmental aspects. Energy efficiency stands for a pivotal resource for economic and social development, yielding critical benefits to different stakeholders. In addition to cost-savings, multiple benefits can be obtained by providing a better balance between energy/environmental issues and strategic business priorities.

 

According to these points of view, new concepts began to spread in the body of literature, namely sustainable development, circular economy, green design, resiliency, and energy awareness. Recently, many researchers have worked on these concepts in different phases of industrial-based Computation Problems (ICP) using Artificial Intelligence (AI) techniques. AI methods, including Artificial Neural Networks (ANN), Machine Learning (ML), Support Vector Machine (SVM), etc. are among the most applicable and efficient tools to study the new requirements of ICP with a wide range of applications.

 

The main aim of this Special Issue is to explore the recent advantages of AI approaches to address the energy and environmental issues in ICP. We invite researchers and practitioners to submit original research and critical survey manuscripts that propose AI approaches on the following potential topics and their applications, but are not limited to:

 

  • Application of machine learning in ICP
  • Application of neural networks and the developed versions in ICP
  • Big data analysis and its application in ICP
  • Fuzzy interface systems and their application in ICP
  • Hybrid stochastic methods and their application in ICP
  • Game theory and its application in ICP
  • Novel heuristic and meta-heuristic algorithms

Important Dates

Full Paper Submission will start on: 1 August 2021

Full Paper Submission will close on: 31 December 2021

 

Lead Editor

Prof. Haytham Bany Salameh

Telecommunications Engineering Department, Yarmouk University, Irbid, Jordan

Email: haythem@yu.edu.jo

 

Haythem Bany Salameh received the Ph.D. degree in electrical and computer engineering from the University of Arizona, Tucson, AZ, USA, in 2009. He is currently a Professor of telecommunication engineering with Yarmouk University (YU), Irbid, Jordan. He was the Director of the Queen Rania Center for Jordanian Studies and Community Service from June 2014 to June 2018. From January 2011 to June 2014, he was the Director of the Academic Entrepreneurship Center of Excellence, YU. In August 2009, he joined YU, after a brief postdoctoral position with the University of Arizona. His current research interests include optical communication technology and wireless networking, with emphasis on dynamic spectrum access, radio resource management, energy-efficient networking, and distributed protocol design. His research covers a wide variety of wireless systems, including cognitive radio networks, wireless sensor networks, ad hoc networks, and cellular networks. He is a recipient of the Jordan Science Research Support Foundation prestigious award for Distinguished Research in ICT sector, 2016. He is also the recipient of the Best Researcher Award for Scientific Colleges in Yarmouk University for the year 2015/2016. Dr. Bany Salameh has served and continues to serve on the Technical Program Committee of many international conferences and serves as a Reviewer for many international conferences and journals. In the summer of 2008, he was a member of the R&D Long-Term Evolution Development Group, QUALCOMM, Inc., San Diego, CA, USA. He is an IEEE Senior Member class of 2016.

 

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