Aim & Scope

Advances in machine learning approaches applied in cyber-physical power systems has gained huge attention in recent days among the research communities. Intelligent learning techniques are aiding large scale critical infrastructures to operate efficiently and securely. The use of Internet of Things (IoT) and expert systems, and autonomous decision making systems are adding layers of interoperability and functionality among the operands of the cyber-physical power systems. New research trends are discovering loopholes and backdoors for unwanted intruders in the complex systems and finding defensive strategies to reduce the loss or protect the system. This special issue will be focusing on the advanced machine learning techniques for intelligent cyber-physical power systems along their approaches and applications.

This special session will provide a unique platform for researchers from different research communities, including artificial intelligence, power and energy, cyber-physical security, intelligent and expert systems, communications, and among others, to share their research expertise towards intelligent cyber-physical power systems. The special session will also enhance the discussion among different communities to explore more challenging cross-domain research topics along this direction.

Topics Covered

• Deep learning techniques for Industry 4.0 wireless sensor networks

• Big data analytics and deep learning for cyber-physical power systems

• Advances in machine learning techniques for secure cyber-physical power systems

• Deep learning techniques for events and anomaly detection

• Learning techniques for adversarial environments in Cyber-physical power systems

• Applications of machine learning for Internet of Things (IoT) devices in cyber-physical power systems

• Intelligent and expert systems for cyber-physical power systems

• Advances in computational intelligence techniques for security of cyber-physical power systems

• Advanced machine learning techniques for cyber-security applications of cyber-physical power systems

• Intelligent machine learning techniques for advanced control and monitoring strategies development

Program Committee

• Organizers:

  • Dr. Shuva Paul, National Renewable Energy Laboratory, Golden, Colorado, USA

  • Dr. Zhen Ni, Florida Atlantic University, Bocaraton, Florida, USA

• Possible Contributors:

  • Dr. Fei Ding (NREL, USA)

  • Dr. Santosh Veda (NREL, USA)

  • Dr. Zhaoyu Wang (Iowa State University, USA)

  • Dr. Akhlaqur Rahman Hridoy (EIT, Australia)

  • Dr. Sumit Paudyal (FIU, USA)

  • Dr. Wei Sun (UCF, USA)

  • Dr. Yufei Tang (FAU, USA)

  • Dr. Tim Hansen (SDSU, USA)

  • Dr. Haibo He (URI, USA)

  • Dr. Jun Yan (Concordia, Canada)

  • Dr. Wei Yao (Huazhong University of Science and Technology, China)

Important Dates

• Submission site: https://ieee-cis.org/conferences/ijcnn2020/upload.php

• Deadline for submission: 30th January, 2020

• Notification of acceptance: 15th March, 2020

• IEEE WCCI 2020: IEEE WCCI 2020, Glasgow, Scotland, UK

Paper Submission

Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of WCCI 2020. The authors who submit papers to this session are invited to select "S58. Advances in Learning Systems for Intelligent Cyber-Physical Power Systems: Approaches and Applications" as their main topic. Submissions to special sessions follow identical format, instructions, deadlines and procedures of regular papers.

For further information and news, please refer to the WCCI 2020 website: https://www.wcci2020.org/