Overview
- Reviews the state-of-the-art of firework algorithms (FWA) as a novel explosive search way for optimization
- Offers the key operators and characteristics as well as theoretical analyses of convergence and time-complexity of FWA through stochastic Markov process
- Presents exhaustively the key recent research into varieties of improving versions of FWA so far
- Enriches understanding of FWA by incorporating FWA with GPU, MOO, and combinatorial optimization
- Covers many different applications including NMF, document clustering, pattern recognition, inversion problem, and swarm robotics
- Includes supplementary material: sn.pub/extras
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Table of contents (17 chapters)
Keywords
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Bibliographic Information
Book Title: Fireworks Algorithm
Book Subtitle: A Novel Swarm Intelligence Optimization Method
Authors: Ying Tan
DOI: https://doi.org/10.1007/978-3-662-46353-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-46352-9Published: 20 October 2015
Softcover ISBN: 978-3-662-51618-8Published: 23 August 2016
eBook ISBN: 978-3-662-46353-6Published: 11 October 2015
Edition Number: 1
Number of Pages: XXXIX, 323
Topics: Artificial Intelligence, Computational Intelligence, Numeric Computing, Robotics and Automation
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