This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9783642101779_new
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Questo è un articolo print on demand. Codice articolo VJ6GIF4LHW
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems. 372 pp. Englisch. Codice articolo 9783642101779
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Da: moluna, Greven, Germania
Condizione: New. Codice articolo 5049152
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Biologically-Inspired Optimisation Methods | Parallel Algorithms, Systems and Applications | Andrew Lewis (u. a.) | Taschenbuch | Studies in Computational Intelligence | xii | Englisch | 2010 | Springer | EAN 9783642101779 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 106954446
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Evolution's Niche in Multi-Criterion Problem Solving.- Applications of Parallel Platforms and Models in Evolutionary Multi-Objective Optimization.- Asynchronous Multi-Objective Optimisation in Unreliable Distributed Environments.- Dynamic Problems and Nature Inspired Meta-heuristics.- Relaxation Labelling Using Distributed Neural Networks.- Extremal Optimisation for Assignment Type Problems.- Niching for Ant Colony Optimisation.- Using Ant Colony Optimisation to Construct Meander-Line RFID Antennas.- The Radio Network Design Optimization Problem.- Strategies for Decentralised Balancing Power.- An Analysis of Dynamic Mutation Operators for Conformational Sampling.- Evolving Computer Chinese Chess Using Guided Learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch. Codice articolo 9783642101779
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems. Codice articolo 9783642101779
Quantità: 1 disponibili