Special Issue "Advanced Developments in Machine Learning for Smart System Analysis"

Submission Deadline: 28 May 2022
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Guest Editors
Dr. Muhammad Adnan Khan, Gachon University, Korea.
Dr. Taher M. Ghazal, University City Sharjah, UAE.
Dr. Sagheer Abbass, National College of Bussiness Administration and Economics, Pakistan.

Summary

As a theme, recent developments in computing machinery have helped us to create smarter surroundings, such as smart cities, smart homes, and smart transportation (e.g., cell phones, robotics, automobiles, etc.). Recently, the new tools and strategies that have been developed to build smart houses and smart communities have given several benefits to modern intelligent solutions such as smart houses and smart vehicles. Conveying with brain-inspired computational Machinery techniques has helped computer-related devices to accomplish great achievements in the IT field.

Here, two major subjects are of considerable importance in the ML area: novel functional ways to deal with the complicated problem of brain-inspired learning, and new advances in machine learning for use in the domain of intelligent systems. In the last few decades, there have been studies of autonomous robots that are capable of human-like conversation and aspects that will be very difficult for a robot to do sometime in the future.

In Global Intelligence Resource, this special issue seeks to present the most current theoretical progress and scientific developments in the vast field of neural networks and adaptive computing systems. The future topics for the paper are wide-ranging and include but are not limited to the following issues.


Keywords
• Deep neural networks and learning
• Applications of neural networks in data analytics
• Smart homes and smart buildings
• Automation and control system
• Smart e-health services
• Smart mobility and transportation
• Extreme Machine Learning
• Deep Learning
• Secure Online Social Networks
• Big Data analytics for IoT systems
• Distributed AI Systems and Architectures
• Cyber & Information Security