Synopsis
The advantage of statistical models of input-output type is that they can be relatively easily constructed and applied, but on the other hand the disadvantage of such models is that that they don’t reveal the inner nature of observed phenomenon. Conceptual models, which have advantage of transparent functioning, but are sometimes hard to be proven correct. Artificial intelligence offers methods of machine learning from examples, which eliminate the disadvantages of statistical as well as conceptual approaches and integrate the advantages. A comprehensive data driven modelling experiment based on regression trees is presented in this book. Regression trees have been employed on practical problem of constructing a data driven model for runoff prediction from known present and past runoff at water-level-gauges and rainfall at rain gauges within the catchment. Results based on approximation and prediction accuracy obtained from regression trees are then compared with other DDM techniques namely, artificial neural networks, Gaussian process, support vector regressions and multiple linear regressions. Book is a must read for the researchers working in the field of data-driven modelling.
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Data-Driven Modelling
Edité par
LAP Lambert Academic Publishing Sep 2017, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The advantage of statistical models of input-output type is that they can be relatively easily constructed and applied, but on the other hand the disadvantage of such models is that that they don't reveal the inner nature of observed phenomenon. Conceptual models, which have advantage of transparent functioning, but are sometimes hard to be proven correct. Artificial intelligence offers methods of machine learning from examples, which eliminate the disadvantages of statistical as well as conceptual approaches and integrate the advantages. A comprehensive data driven modelling experiment based on regression trees is presented in this book. Regression trees have been employed on practical problem of constructing a data driven model for runoff prediction from known present and past runoff at water-level-gauges and rainfall at rain gauges within the catchment. Results based on approximation and prediction accuracy obtained from regression trees are then compared with other DDM techniques namely, artificial neural networks, Gaussian process, support vector regressions and multiple linear regressions. Book is a must read for the researchers working in the field of data-driven modelling. 68 pp. Englisch. N° de réf. du vendeur 9786202016353
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Data-Driven Modelling: Investigation of data-driven flood forecasting models
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LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock. N° de réf. du vendeur zk6202016353
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Data-Driven Modelling
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LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
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Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tufail Sohail AhmedSohail Ahmed was born in Shikarpur, Pakistan, on January 01, 1990. After finishing high school in 2008, he studied Civil Engineering at University of Engineering and Technology Lahore. He received M.Sc in Hydro Sci. N° de réf. du vendeur 166521635
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Data-Driven Modelling
Edité par
LAP Lambert Academic Publishing Sep 2017, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -The advantage of statistical models of input-output type is that they can be relatively easily constructed and applied, but on the other hand the disadvantage of such models is that that they don¿t reveal the inner nature of observed phenomenon. Conceptual models, which have advantage of transparent functioning, but are sometimes hard to be proven correct. Artificial intelligence offers methods of machine learning from examples, which eliminate the disadvantages of statistical as well as conceptual approaches and integrate the advantages. A comprehensive data driven modelling experiment based on regression trees is presented in this book. Regression trees have been employed on practical problem of constructing a data driven model for runoff prediction from known present and past runoff at water-level-gauges and rainfall at rain gauges within the catchment. Results based on approximation and prediction accuracy obtained from regression trees are then compared with other DDM techniques namely, artificial neural networks, Gaussian process, support vector regressions and multiple linear regressions. Book is a must read for the researchers working in the field of data-driven modelling.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. N° de réf. du vendeur 9786202016353
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Data-Driven Modelling : Investigation of data-driven flood forecasting models
Edité par
LAP Lambert Academic Publishing, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The advantage of statistical models of input-output type is that they can be relatively easily constructed and applied, but on the other hand the disadvantage of such models is that that they don't reveal the inner nature of observed phenomenon. Conceptual models, which have advantage of transparent functioning, but are sometimes hard to be proven correct. Artificial intelligence offers methods of machine learning from examples, which eliminate the disadvantages of statistical as well as conceptual approaches and integrate the advantages. A comprehensive data driven modelling experiment based on regression trees is presented in this book. Regression trees have been employed on practical problem of constructing a data driven model for runoff prediction from known present and past runoff at water-level-gauges and rainfall at rain gauges within the catchment. Results based on approximation and prediction accuracy obtained from regression trees are then compared with other DDM techniques namely, artificial neural networks, Gaussian process, support vector regressions and multiple linear regressions. Book is a must read for the researchers working in the field of data-driven modelling. N° de réf. du vendeur 9786202016353
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Data-Driven Modelling | Investigation of data-driven flood forecasting models
Edité par
LAP Lambert Academic Publishing, 2017
ISBN 10 : 6202016353
ISBN 13 : 9786202016353
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. Data-Driven Modelling | Investigation of data-driven flood forecasting models | Sohail Ahmed Tufail | Taschenbuch | 68 S. | Englisch | 2017 | LAP Lambert Academic Publishing | EAN 9786202016353 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 109680319
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