Guest Editor(s)
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- Dr. Deepak Gupta
National Institute of Technology, India.
Website | E-mail
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- Prof. Qin Xin
University of the Faroe Islands, Faroe Islands.
Website | E-mail
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- Dr. Deepak Puthal
Newcastle University, United Kingdom.
Website | E-mail
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- Dr. Mukesh Prasad
University of Technology Sydney, Australia.
Website | E-mail
Special Issue Introduction
Machine Learning and Computational Intelligence (MLCI) constitutes an umbrella of techniques, which has proven to be flexible in solving dynamic and complex real-world problems. These techniques typically include neural networks and learning algorithms, fuzzy systems, evolutionary computation and other emerging techniques for dealing with uncertainties encountered in evolutionary optimization, machine learning and data mining. The MLCI techniques are also widely used in Green Computing applications such as Internet of Things, Building Smart Cities, Digital health, Smart education, Smart Agriculture and some more towards sustainable computing infrastructure at different levels. The MLCI techniques enable complex learning, planning, and decision-making problems in a centralized/decentralized fashion. It is able to execute large-scale computation through distributed computing resources. These properties allow it to solve problems that require the processing of very large data sets. This approach, when put together with the idea of Green Computing, opens up a new world of applications of artificial intelligence in a localized manner. It is clear that MLCI is going to play a huge role in the lives of the average human being. We can also be sure that the intelligence that will run the world will be far more advanced and heuristic than the kind we have today.
The main topics of this special session include, but are not limited to the following:
• MLCI Data Driven Approach for Edge, Fog and Cloud Computing
• Addressing Security, Privacy and Trust in Edge, Fog and Cloud Datacentres
• Vehicular Edge/Fog/Cloud Computing for Smart Cities
• AI Enabled Big Data for Edge, Fog and Cloud Computing
• MLCI for Smart Education, Agriculture and Health
• MLCI Approach for Energy Efficient in IoT
• Application of MLCI for Smart Manufacturing
Submission Deadline
31 Mar 2022