Applied Nature-Inspired Computing: Algorithms and Case Studies (Springer Tracts in Nature-Inspired Computing)
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Fulfillment optionsApplied Nature-Inspired Computing
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.
Details
- Publisher
- Springer Nature Singapore
- Format
- Hardcover
- Published
- Aug 24, 2019
- ISBN-13
- 9789811392627
- Pages
- 275
- Printing
- Printed on demand
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| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $96.79 | 12% off list |
| 50 – 99 | $95.69 | 13% off list |
| 100+ | $94.59 | 14% off list |
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Applied Nature-Inspired Computing: Algorithms and Case Studies (Springer Tracts in Nature-Inspired Computing)
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