大葉大學圖書館 |

Nature-inspired computation in engineering[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3824
書名/作者:	Nature-inspired computation in engineering/ edited by Xin-She Yang.
其他作者:	Yang, Xin-She.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	x, 276 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Swarm intelligence.
標題:	Computer algorithms.
標題:	Biologically-inspired computing.
標題:	Artificial intelligence - Engineering applications.
標題:	Engineering.
標題:	Computational Intelligence.
標題:	Artificial Intelligence (incl. Robotics)
ISBN:	9783319302355
ISBN:	9783319302331
內容註:	Flower Pollination Algorithm and its Applications in Engineering -- An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with TimeWindows -- The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem -- Enhancing Cooperative Coevolution with Surrogate-Assisted Local Search -- Cuckoo Search: From Cuckoo Reproduction Strategy to Combinatorial 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.
摘要、提要註:	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 serve as a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.
電子資源:	http://dx.doi.org/10.1007/978-3-319-30235-5

Nature-inspired computation in engineering[electronic resource] /
Nature-inspired computation in engineering[electronic resource] /edited by Xin-She Yang. - Cham :Springer International Publishing :2016. - x, 276 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6371860-949X ;. - Studies in computational intelligence ;v.379..

Flower Pollination Algorithm and its Applications in Engineering -- An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with TimeWindows -- The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem -- Enhancing Cooperative Coevolution with Surrogate-Assisted Local Search -- Cuckoo Search: From Cuckoo Reproduction Strategy to Combinatorial 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.

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 serve as a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.

ISBN: 9783319302355

Standard No.: 10.1007/978-3-319-30235-5doiSubjects--Topical Terms:

470574
Swarm intelligence.

LC Class. No.: Q337.3

Dewey Class. No.: 006.3824

Nature-inspired computation in engineering[electronic resource] /
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520 $a 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 serve as a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.
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