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Handbook of Swarm Intelligence: Concepts, Principles and Applications: 8 (Adaptation, Learning, and Optimization) - Tapa blanda
Sinopsis
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.
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From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.
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Handbook of Swarm Intelligence: Concepts, Principles and Applications (Adaptation, Learning, and Optimization, 8)
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Handbook of Swarm Intelligence: Concepts, Principles and Applications (Adaptation, Learning, and Optimization, 8)
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Handbook of Swarm Intelligence : Concepts, Principles and Applications
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Handbook of Swarm Intelligence
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Springer Berlin Heidelberg, 2013
ISBN 10: 3642266894
ISBN 13: 9783642266898
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Tapa blanda
Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive study of both theoretical and algorithmic analysis of swarm intelligence techniques. Provides real-world applications of SI techniquesWritten by leading experts in this fieldFrom nature, we observe swarming behav. Nº de ref. del artículo: 5054740
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Handbook of Swarm Intelligence (Paperback)
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Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2013
ISBN 10: 3642266894
ISBN 13: 9783642266898
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Paperback. Condición: new. Paperback. From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving. From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783642266898
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Handbook of Swarm Intelligence: Concepts, Principles and Applications (Adaptation, Learning, and Optimization, 8)
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Handbook of Swarm Intelligence
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Springer Berlin Heidelberg Feb 2013, 2013
ISBN 10: 3642266894
ISBN 13: 9783642266898
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Taschenbuch
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving. 556 pp. Englisch. Nº de ref. del artículo: 9783642266898
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Handbook of Swarm Intelligence : Concepts, Principles and Applications
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 19786680
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Handbook of Swarm Intelligence: Concepts, Principles and Applications (Adaptation, Learning, and Optimization, 8)
Librería: California Books, Miami, FL, Estados Unidos de America
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Condición: New. Nº de ref. del artículo: I-9783642266898
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Handbook of Swarm Intelligence
Publicado por
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2013
ISBN 10: 3642266894
ISBN 13: 9783642266898
Nuevo
Tapa blanda
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Condición: New. Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational problem-solving techniques. This volume is both an introduction to the topic and a survey of leading-edge research. Editor(s): Panigrahi, Bijaya Ketan; Shi, Yuhui; Lim, Meng-Hiot. Series: Adaptation, Learning, and Optimization. Num Pages: 556 pages, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 29. Weight in Grams: 842. . 2013. Paperback. . . . . Nº de ref. del artículo: V9783642266898
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