2014, ISBN: 3319092340
[EAN: 9783319092348], Neubuch, [PU: Springer International Publishing Nov 2014], GEOLOGIE / HYDROGEOLOGIE; HYDROGEOLOGIE - HYDROLOGIE; BAU TIEFBAU; APPLIEDHYDROLOGY; ARTIFICIALINTELLIGENC… Altro …
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Hydrological Data Driven Modelling | A Case Study Approach | Jimson Mathew (u. a.) | Buch | Earth Systems Data and Models | HC runder Rücken kaschiert | XV | Englisch | 2014 | EAN 9783319092348 - copertina rigida, flessible
2014, ISBN: 9783319092348
[ED: Gebunden], [PU: Springer International Publishing], This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents … Altro …
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2015, ISBN: 9783319092348
[ED: Hardcover], [PU: Springer / Springer International Publishing / Springer, Berlin], This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a ca… Altro …
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2017, ISBN: 9783319092348
[ED: Buch], [PU: Springer International Publishing], Neuware - This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it pre… Altro …
booklooker.de |
2015, ISBN: 3319092340
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… Altro …
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2014, ISBN: 3319092340
[EAN: 9783319092348], Neubuch, [PU: Springer International Publishing Nov 2014], GEOLOGIE / HYDROGEOLOGIE; HYDROGEOLOGIE - HYDROLOGIE; BAU TIEFBAU; APPLIEDHYDROLOGY; ARTIFICIALINTELLIGENC… Altro …
Mathew, Jimson:
Hydrological Data Driven Modelling | A Case Study Approach | Jimson Mathew (u. a.) | Buch | Earth Systems Data and Models | HC runder Rücken kaschiert | XV | Englisch | 2014 | EAN 9783319092348 - copertina rigida, flessible2014, ISBN: 9783319092348
[ED: Gebunden], [PU: Springer International Publishing], This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents … Altro …
2015
ISBN: 9783319092348
[ED: Hardcover], [PU: Springer / Springer International Publishing / Springer, Berlin], This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a ca… Altro …
2017, ISBN: 9783319092348
[ED: Buch], [PU: Springer International Publishing], Neuware - This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it pre… Altro …
2015, ISBN: 3319092340
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… Altro …
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Informazioni dettagliate del libro - Hydrological Data Driven Modelling
EAN (ISBN-13): 9783319092348
ISBN (ISBN-10): 3319092340
Copertina rigida
Anno di pubblicazione: 2014
Editore: Springer International Publishing
Libro nella banca dati dal 2014-10-10T07:00:28+02:00 (Rome)
Pagina di dettaglio ultima modifica in 2023-12-07T17:06:19+01:00 (Rome)
ISBN/EAN: 9783319092348
ISBN - Stili di scrittura alternativi:
3-319-09234-0, 978-3-319-09234-8
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : jim, mathew
Titolo del libro: driven, modelling the, case study
Dati dell'editore
Autore: Renji Remesan; Jimson Mathew
Titolo: Earth Systems Data and Models; Hydrological Data Driven Modelling - A Case Study Approach
Editore: Springer; Springer International Publishing
250 Pagine
Anno di pubblicazione: 2014-11-17
Cham; CH
Stampato / Fatto in
Lingua: Inglese
128,39 € (DE)
131,99 € (AT)
142,00 CHF (CH)
POD
XV, 250 p. 172 illus., 59 illus. in color.
BB; Hardcover, Softcover / Geowissenschaften/Geologie; Geologie und die Lithosphäre; Verstehen; Applied hydrology; Artificial intelligence in hydrology; Evapotranspiration modelling; Hydrologic modelling; Rainfall-Runoff modelling; Solar radiation; Support vector; Time series modelling; hydrogeology; Geology; Water; Geoengineering; Hydrologie und die Hydrosphäre; Konstruktiver Ingenieurbau, Baustatik; EA; BC
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.
Introduction.- Hydroinformatics and Data based Modelling Issues in Hydrology.- Hydroinformatics and Data based Modelling Issues in Hydrology.- Model Data Selection and Data Pre-processing Approaches.- Machine Learning and Artificial Intelligence Based Approaches.- Data based Solar Radiation Modelling.- Data based Rainfall-Runoff Modelling.- Data based Evapotranspiration Modelling.- Application of Statistical Blockade in Hydrology.
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.
Covers many aspects of data based modelling issues with application to Hydrology Brings readers up to date with clear case studies Enables engineers to appropriately identify modelling approaches and issues Includes supplementary material: sn.pub/extras
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