9783030647766 - deep learning for hydrometeorology and environmental science: 99 (water science and technology library, 99) de lee, taesam; singh, vijay p.; cho, kyung hwa (13 resultados)
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Condición: 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)
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 218 pages. 9.25x6.10x0.67 inches. In Stock.
Idioma: Inglés
Editorial: Springer International Publishing 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Buch. Condición: 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 datas…ets 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.
Idioma: Inglés
Editorial: SPRINGER NP 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Condición: 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 th…e Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
Idioma: Inglés
Editorial: Springer International Publishing Jan 2021 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: 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 examples… 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.
Idioma: Inglés
Editorial: Springer International Publishing 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: moluna, Greven, , Alemaniamoluna
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Condición: 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 Co…vers major deep le.
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Springer 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND.
Idioma: Inglés
Editorial: Springer, Springer Jan 2021 2021
Serie: Water Science and Technology Library, Libro 88 de 101. Libro 88 de 101 - Water Science and Technology Library
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 128,39
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Buch. Condición: 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 wit…h 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.
