Applied Nature-Inspired Computing: Algorithms and Case Studies
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 nat…
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Produktdetails
Weitere Autoren: Ashour, Amira S. (Hrsg.) / Bhattacharyya, Siddhartha (Hrsg.)
- ISBN: 978-981-1392-62-7
- EAN: 9789811392627
- Produktnummer: 31751620
- Verlag: Springer Nature EN
- Sprache: Englisch
- Erscheinungsjahr: 2019
- Seitenangabe: 275 S.
- Masse: H23.5 cm x B15.5 cm 0 g
- Auflage: 1st ed. 2020
- Abbildungen: Farb., s/w. Abb.
- Sonstiges: Research
Über den Autor
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