Applied Nature-Inspired Computing: Algorithms and Case Studies Paperback / softback
Edited by Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya
Part of the Springer Tracts in Nature-Inspired Computing series
Paperback / softback
Description
This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications.
It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems.
In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
Information
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Out of stock
- Format:Paperback / softback
- Pages:275 pages, 89 Illustrations, color; 45 Illustrations, black and white; XII, 275 p. 134 illus., 89 il
- Publisher:Springer Verlag, Singapore
- Publication Date:25/08/2020
- Category:
- ISBN:9789811392658
Information
-
Out of stock
- Format:Paperback / softback
- Pages:275 pages, 89 Illustrations, color; 45 Illustrations, black and white; XII, 275 p. 134 illus., 89 il
- Publisher:Springer Verlag, Singapore
- Publication Date:25/08/2020
- Category:
- ISBN:9789811392658
