Intelligent Data-Driven Systems and Artificial Intelligence

About the Book Series

Series Editor: Harish Garg, Thapar Institute of Engineering & Technology (Deemed University), Punjab, India

Editorial Board members:

Prof. Radu-Emil Precup, Department of Automation and Applied Informatics, Romania

Prof. Luis Martínez, University of Jaén, Jaén, Spain

Prof. Yanhui Guo, University of Illinois Springfield, USA

Prof. Dragan Pamucar, University of Defence in Belgrade, Serbia

Prof. Cengiz Kahraman, Istanbul Technical University, Turkey

Prof. Mohammad Yazdi, Macquarie University, Australia

Prof. Nargiz Safarova, Baku State University, Baku, Azerbaijan

Prof. Graçaliz Pereira Dimuro, Federal University of Rio Grande, Brazil

Prof. Jurgita Antucheviciene, Vilnius Gediminas Technical University, Lithuania

Prof. Aslıhan Sezgin, Amasya University, Türkiye.

Online ISSN: 3066-7291

Print ISSN: 3066-7305

About the Series

In today's era, most companies have adopted data-driven policies for operational decision-making. As a result, data-driven decision-making approaches are becoming increasingly important, along with the use of artificial intelligence. The aim of this series is to discuss cutting-edge technologies and explain their significance in terms of models, algorithms, and theoretical concepts related to intelligent data-driven systems and artificial intelligence. The series covers research on various databases and their applications in machine learning, decision-support systems, artificial intelligence, knowledge-based systems, and pattern recognition. It further explores the use of data analytics, meta-heuristic search, planning and scheduling, artificial neural networks, evolutionary computation, and swarm intelligence for intelligent systems. The books published under this series will be valuable for senior graduate students, graduate students, academic researchers, and professionals in the fields of computer engineering, electrical engineering, information technology, and related disciplines.

Salient Features:

• Covers models, algorithms, and theoretical concepts of intelligent data-driven systems and artificial intelligence.
• Explores challenges and issues encountered by the academicians and researchers while working in the field of real-time analytics.
• Showcases books in key areas including cognitive and soft computing-based data-centric operations, pattern recognition, and computer vision.
• Highlights different data-driven systems and artificial intelligence platforms for real-life problems.