This book aims at providing theoretical knowledge in the application of swarm intelligence and evolutionary computation including several recent meta-heuristic algorithms and also providing practical emerging applications in machine learning and deep learning.
This book aims at providing theoretical knowledge in the application of swarm intelligence and evolutionary computation including several recent meta-heuristic algorithms and also providing practical emerging applications in machine learning and deep learning.
Georgios N. Kouziokas is a Lecturer at the University of Thessaly, Greece. He holds a Ph.D. in artificial intelligence in decision systems from the University of Thessaly. He holds four Masters of Science (MSc) in: computer science, applied mathematics, education, geographic information systems and environmental spatial analysis and a BSc in computer science. He serves as an editor in two international journals about the application of artificial intelligence, editorial board member and associate editor in several international journals. He has reviewed for more than 60 international journals. He was awarded with the Emerging Scholar Award 2018 by the University of Illinois, USA for his Ph.D. achievements. Also, he was awarded with the Top Peer Reviewer Award 2018, 2019 by Publons organization, part of Web of Science. He has more than 45 publications in peer-reviewed international scientific journals, book chapters and conference proceedings from major publishers, like Elsevier and Springer. He has served as a member of the organizing committee, program chair in several international conferences. His major research areas include work related to Artificial Intelligence, Computational Intelligence and Optimization, Swarm Intelligence, Machine Learning, Deep Learning, Neuro-Fuzzy Logic, Applied Mathematics, Information Systems, Educational Informatics, Environmental Informatics, Data Analysis, AI in Education, AI in Public Management, AI in justice, AI in Image Processing/Remote Sensing - Geographic Information Systems, Robotics, Quantum Artificial Intelligence and Cyber-Security.
Inhaltsangabe
1. Computational optimization 2. Evolutionary Computation and Genetic Algorithm 3. Swarm Intelligence and Particle Swarm Optimization 4. Ant Colony Optimization and Artificial Bee Colony 5. Cuckoo Search and Bat Swarm Algorithm 6. Firefly Algorithm, Harmony Search and Cat Swarm Algorithm 7. Grey Wolf, Whale and Grasshopper Optimization 8. Machine Learning Optimization Applications 9. Swarm and Evolutionary Intelligence in Deep Learning
