9783030647766 - deep learning for hydrometeorology and environmental science: 99 di lee, taesam; singh, vijay p.; cho, kyung hwa (12 risultati)
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: SpringBooks, Berlin, GermaniaSpringBooks
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Hardcover. Condizione: Very Good. 1. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Deep Learning for Hydrometeorology and Environmental Science
Lee, Taesam (Author)/ Singh, Vijay P. (Author)/ Cho, Kyung Hwa (Author)
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
- Rilegato
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 218 pages. 9.25x6.10x0.67 inches. In Stock.
Lingua: Inglese
Editore: Springer International Publishing, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real data…sets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited.Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.
Lingua: Inglese
Editore: SPRINGER NP, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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- Edizione Internazionale
Da: UK BOOKS STORE, London, LONDO, Regno UnitoUK BOOKS STORE
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Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if t…he Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing Jan 2021, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as example…s with real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited.Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model. 220 pp. Englisch.
Lingua: Inglese
Editore: Springer International Publishing, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides step-by-step tutorials that help the reader to learn complex deep learning algorithmsGives an explanation of deep learning techniques and their applications to hydrometeorological and environmental studies C…overs major deep le.
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Springer Jan 2021, 2021
Serie: Water Science and Technology Library, Libro 88 di 101. Libro 88 di 101 - Water Science and Technology Library
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 128,39
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples wi…th real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality).Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited.Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare.This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 220 pp. Englisch.
