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Hydrological Data Driven Modelling | Remesan / Mathew - Buch - Renji Remesan, Jimson Mathew - Renji Remesan, Jimson Mathew
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Renji Remesan, Jimson Mathew:
Hydrological Data Driven Modelling | Remesan / Mathew - Buch - Renji Remesan, Jimson Mathew - neues Buch

ISBN: 9783319092348

ID: 14049354

Von Renji Remesan, Jimson Mathew: This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.; Weitere Fachgebiete > Geologie, Geographie, Klima, Umwelt > Geologie > Hydrologie, Hydrogeologie, Springer

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Hydrological Data Driven Modelling - Renji Remesan
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Renji Remesan:
Hydrological Data Driven Modelling - neues Buch

ISBN: 9783319092348

ID: 21542d7ce3dfa85b03dfb01c53aa0e83

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Geowissenschaften / Sonstiges

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Hydrological Data Driven Modelling - Mathew, Jimson; Remesan, Renji
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Mathew, Jimson; Remesan, Renji:
Hydrological Data Driven Modelling - neues Buch

ISBN: 9783319092348

ID: 1966875

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space. Science Science eBook, Springer International Publishing

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Hydrological Data Driven Modelling - Renji Remesan
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Renji Remesan:
Hydrological Data Driven Modelling - neues Buch

2014, ISBN: 9783319092348

[ED: Buch], [PU: Springer-Verlag GmbH], Neuware - This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space., [SC: 0.00]

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Hydrological Data Driven Modelling A Case Study Approach - Remesan, Renji; Mathew, Jimson
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Remesan, Renji; Mathew, Jimson:
Hydrological Data Driven Modelling A Case Study Approach - gebunden oder broschiert

2014, ISBN: 3319092340

ID: A22597088

Gebundene Ausgabe Geologie / Hydrogeologie, Hydrogeologie - Hydrologie, Hydrologie ( Hydrogeologie ), Bau / Tiefbau, Tiefbau, SCIENCE / Earth Sciences / Hydrology, mit Schutzumschlag neu, [PU:Springer-Verlag GmbH]

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