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Applied nature-inspired computing : algorithms and case studies / Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors.

9789811392634 (electronic book)
9811392633 (electronic book)
9789811392627

Singapore : Springer, 2020.

English

1 online resource (281 pages)

10.1007/978-981-13-9

QA76.9.N37

006.3/82

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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Description based on print version record.

Springer Tracts in Nature-Inspired Computing.

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