Applied Nature-Inspired Computing: Algorithms and Case Studies

Applied Nature-Inspired Computing: Algorithms and Case Studies - Springer Tracts in Nature-Inspired Computing

1st Edition 2020

Paperback (25 Aug 2020)

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Publisher's Synopsis

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.


Book information

ISBN: 9789811392658
Publisher: Springer Nature Singapore
Imprint: Springer
Pub date:
Edition: 1st Edition 2020
Language: English
Number of pages: 275
Weight: 444g
Height: 235mm
Width: 155mm
Spine width: 15mm