Nature-Inspired Computation in Engineering
Series: Studies in Computational Intelligence; 637;
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45 385 Ft
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Product details:
- Edition number 1st ed. 2016
- Publisher Springer
- Date of Publication 30 March 2016
- Number of Volumes 1 pieces, Book
- ISBN 9783319302331
- Binding Hardback
- No. of pages276 pages
- Size 235x155 mm
- Weight 5561 g
- Language English
- Illustrations 20 Illustrations, black & white; 34 Illustrations, color 0
Categories
Short description:
This timely review book summarizes the
state-of-the-art developments in nature-inspired optimization algorithms and
their applications in engineering. Algorithms and topics include the overview
and history of nature-inspired algorithms, discrete firefly algorithm, discrete
cuckoo search, plant propagation algorithm, parameter-free bat algorithm,
gravitational search, biogeography-based algorithm, differential evolution,
particle swarm optimization and others. Applications include vehicle routing,
swarming robots, discrete and combinatorial optimization, clustering of
wireless sensor networks, cell formation, economic load dispatch, metamodeling,
surrogated-assisted cooperative co-evolution, data fitting and reverse
engineering as well as other case studies in engineering. This book will be an
ideal reference for researchers, lecturers, graduates and engineers who are
interested in nature-inspired computation, artificial intelligence and
computational intelligence. It can also serveas a reference for relevant
courses in computer science, artificial intelligence and machine learning, natural
computation, engineering optimization and data mining.
More
Long description:
This timely review book summarizes the
state-of-the-art developments in nature-inspired optimization algorithms and
their applications in engineering. Algorithms and topics include the overview
and history of nature-inspired algorithms, discrete firefly algorithm, discrete
cuckoo search, plant propagation algorithm, parameter-free bat algorithm,
gravitational search, biogeography-based algorithm, differential evolution,
particle swarm optimization and others. Applications include vehicle routing,
swarming robots, discrete and combinatorial optimization, clustering of
wireless sensor networks, cell formation, economic load dispatch, metamodeling,
surrogated-assisted cooperative co-evolution, data fitting and reverse
engineering as well as other case studies in engineering. This book will be an
ideal reference for researchers, lecturers, graduates and engineers who are
interested in nature-inspired computation, artificial intelligence and
computational intelligence. It can also serveas a reference for relevant
courses in computer science, artificial intelligence and machine learning, natural
computation, engineering optimization and data mining.
More
Table of Contents:
Flower Pollination Algorithm and its Applications in Engineering.- An Evolutionary Discrete Firefly Algorithm with
Optimization.- Clustering Optimization for WSN based on Nature-Inspired Algorithms.- Discrete Firefly Algorithm for Recruiting Task in a Swarm of Robots.- Nature-Inspired Swarm Intelligence for Data Fitting in Reverse Engineering: Recent Advances and FutureTrends.- A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta-
Modelling Approach.- A Hybridization of Runner-Based and Seed-Based Plant Propagation
Algorithm.- Gravitational Search Algorithm Applied to Cell Formation Problem.- Parameterless Bat Algorithm and its Performace Study.
Nature-Inspired Computation in Engineering
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