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Applied Nature-Inspired Computing: Algorithms and Case Studies (2020)

Contributor(s): Dey, Nilanjan (Editor), Ashour, Amira S (Editor), Bhattacharyya, Siddhartha (Editor)

ISBN: 9789811392627

Publisher: Springer

Hardcover
$109.99
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Pub Date: August 24, 2019

Dewey: 003.3

Lexile Code: 0000

Features: Illustrated

Target Age Group: NA to NA

Physical Info: 0.69" H x 9.21" L x 6.14" W ( 1.28 lbs) 275 pages

Series: Springer Tracts in Nature-Inspired Computing

Descriptions, Reviews, etc.

Description:

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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