Swarm Intelligence: Principles, Advances, and Applications - Tapa dura

Acerca del autor

Aboul Ella Hassanien is a full professor in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. Widely published and highly decorated, he is the founder and chair of the Scientific Research Group in Egypt, has established the Egyptian Rough Sets Society, and is chairing the Egyptian International Rough Set Society Chapter. He has served as a general chair, co-chair, program chair, and program committee member of various international conferences, and as a reviewer and guest editor for numerous international journals. His research interests include computational intelligence, network security, animal identification, and more.

Eid Emary is currently a lecturer in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. He has authored or co-authored more than 15 research publications in peer-reviewed journals, book chapters, and conference proceedings. He has served as a technical program committee member of various international conferences, and as a reviewer for numerous international journals. His research interests are in the areas of computer vision, mathematical optimization, pattern recognition, video and image processing, machine learning, data mining, and biometrics.

De la contraportada

This book delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The text begins by addressing basic concepts related to swarm intelligence, such as randomness and chaos theory. It then describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible. The book not only details the similarities, differences, weaknesses, and strengths of each method, but also depicts real-world applications, emphasizing variable selection and fitness function design.