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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 292 | Sprache: Englisch | Produktart: Bücher | In this book, an easily understandable account of modelling methods with artificial neuronal networks for practical applications in ecology and evolution is provided. Special features include examples of applications using both supervised and unsupervised training, comparative analysis of artificial neural networks and conventional statistical methods, and proposals to deal with poor datasets. Extensive references and a large range of topics make this book a useful guide for ecologists, evolutionary ecologists and population geneticists.
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Condition: New. Discusses modelling theory and applicationIllustrates process-based models as well as machine learning modelsExplains practical guides to apply modelsRedaktion: Young-Seuk ParkYoung-Seuk Park is a Professor a.
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Taschenbuch. Condition: Neu. Artificial Neuronal Networks | Application to Ecology and Evolution | Sovan Lek (u. a.) | Taschenbuch | xxvi | Englisch | 2012 | Springer | EAN 9783642631160 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, an easily understandable account of modelling methods with artificial neuronal networks for practical applications in ecology and evolution is provided. Special features include examples of applications using both supervised and unsupervised training, comparative analysis of artificial neural networks and conventional statistical methods, and proposals to deal with poor datasets. Extensive references and a large range of topics make this book a useful guide for ecologists, evolutionary ecologists and population geneticists.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, an easily understandable account of modelling methods with artificial neuronal networks for practical applications in ecology and evolution is provided. Special features include examples of applications using both supervised and unsupervised training, comparative analysis of artificial neural networks and conventional statistical methods, and proposals to deal with poor datasets. Extensive references and a large range of topics make this book a useful guide for ecologists, evolutionary ecologists and population geneticists.
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