Applied nature-inspired computing : algorithms and case studies / Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors.
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 optimi...
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| Other Authors: | , , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Singapore :
Springer,
2020.
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| Series: | Springer Tracts in Nature-Inspired Computing.
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| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | 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. |
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| Item Description: | 5 Conclusion. Description based upon print version of record. |
| Physical Description: | 1 online resource (281 pages). |
| ISBN: | 9789811392627 9789811392634 9811392625 9811392633 |