Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Title
Advances in swarm intelligence : variations and adaptations for optimization problems / Anupam Biswas, Can B. Kalayci, Seyedali Mirjalili, editors.
ISBN
9783031098352 (electronic bk.)
3031098358 (electronic bk.)
9783031098345
303109834X
Published
Cham, Switzerland : Springer, [2023]
Language
English
Description
1 online resource : illustrations (black and white, and color).
Other Standard Identifiers
10.1007/978-3-031-09835-2 doi
Call Number
Q337.3
Dewey Decimal Classification
006.3/824
Summary
Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. This book emphasizes the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adaptations in the SI techniques. The book will be beneficial for academicians and researchers from various disciplines of engineering and science working in applications of SI and other optimization problems.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Studies in computational intelligence ; v. 1054.
A Brief Tutorial on Optimization Problems, Optimization Algorithms, Meta-heuristics, and Swarm Intelligence
Introductory Review of Swarm Intelligence Techniques
Swarm Intelligence for Deep Learning: Concepts, Challenges and Recent Trends
Advances on Particle Swarm Optimization in Solving Discrete Optimization Problems
Performance Analysis of Hybrid Memory Based Dragonfly Algorithm in Engineering Problems.
