
Applied Nature-Inspired Computing: Algorithms and Case Studies
Format: Hardcover
ISBN13: 9789811392627
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Overview
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.
| ISBN-13 | 9789811392627 |
|---|---|
| ISBN-10 | 9811392625 |
| Weight | 1.28 Pounds |
| Dimensions | 6.25 x 1.00 x 9.25 In |
| List Price | $109.99 |
| Edition | 1st Edition |
| Format | Hardcover |
|---|---|
| Language | English |
| Pages | xii, 275 pages |
| Publisher | Springer |
| Published On | 2019-08-24 |
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Sparks, NV, USA
Free delivery by: 30 Mar 2026