9789811997358 - application of machine learning models in agricultural and meteorological sciences de ehteram, mohammad; seifi, akram; banadkooki, fatemeh barzegari (9 resultados)

Application of Machine Learning Models in Agricultural and Meteorological Sciences
Ehteram, Mohammad; Seifi, Akram; Banadkooki, Fatemeh Barzegari
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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Condición: New. 2023rd edition NO-PA16APR2015-KAP.

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Taschenbuch. Condición: Neu. Application of Machine Learning Models in Agricultural and Meteorological Sciences | Mohammad Ehteram (u. a.) | Taschenbuch | xi | Englisch | 2024 | Springer | EAN 9789811997358 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]spr…inger[dot]com | Anbieter: preigu.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the modelling process are explained in this book. The models o…f the current book help better agriculture and irrigation management. The models of the current book are valuable for meteorological organizations.Meteorological and agricultural variables can be accurately estimated with this book's advanced models. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and evolutionary machine learning to better plan and manage agriculture fields. Water companies and universities can use this book to develop agricultural and meteorological sciences. The details of the modeling process are explained in this book for modelers. Also this book introduces new and advanced models for predicting hydrological variables. Predicting hydrological variables help water resource planning and management. These models can monitor droughts to avoid water shortage. And this contents can be related to SDG6, clean water and sanitation. The book explains how modelers use evolutionary algorithms to develop machine learning models. The book presents the uncertainty concept in the modeling process. New methods are presented for comparing machine learning models in this book. Models presented in this book can be applied in different fields. Effective strategies are presented for agricultural and water management. The models presented in the book can be applied worldwide and used in any region of the world.The models of the current books are new and advanced. Also, the new optimization algorithms of the current book can be used for solving different and complex problems. This book can be used as a comprehensive handbook in the agricultural and meteorological sciences. This book explains the different levels of the modeling process for scholars.

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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.

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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the modelling process are explained in this bo…ok. The models of the current book help better agriculture and irrigation management. The models of the current book are valuable for meteorological organizations.Meteorological and agricultural variables can be accurately estimated with this book's advanced models. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and evolutionary machine learning to better plan and manage agriculture fields. Water companies and universities can use this book to develop agricultural and meteorological sciences. The details of the modeling process are explained in this book for modelers. Also this book introduces new and advanced models for predicting hydrological variables. Predicting hydrological variables help water resource planning and management. These models can monitor droughts to avoid water shortage. And this contents can be related to SDG6, clean water and sanitation. The book explains how modelers use evolutionary algorithms to develop machine learning models. The book presents the uncertainty concept in the modeling process. New methods are presented for comparing machine learning models in this book. Models presented in this book can be applied in different fields. Effective strategies are presented for agricultural and water management. The models presented in the book can be applied worldwide and used in any region of the world.The models of the current books are new and advanced. Also, the new optimization algorithms of the current book can be used for solving different and complex problems. This book can be used as a comprehensive handbook in the agricultural and meteorological sciences. This book explains the different levels of the modeling process for scholars. 208 pp. Englisch.

Application of Machine Learning Models in Agricultural and Meteorological Sciences
Ehteram, Mohammad|Seifi, Akram|banadkooki, Fatemeh barzegari
Idioma: Inglés
Editorial: Springer, Berlin|Springer Nature Singapore|Springer, 2024
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Librería: moluna, Greven, Alemaniamoluna
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the mo…delling process are explained in this book. The models of the .

Application of Machine Learning Models in Agricultural and Meteorological Sciences
Ehteram, Mohammad; Seifi, Akram; Banadkooki, Fatemeh Barzegari
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the modelling process are explained in this book.…The models of the current book help better agriculture and irrigation management. The models of the current book are valuable for meteorological organizations.Meteorological and agricultural variables can be accurately estimated with this book's advanced models. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and evolutionary machine learning to better plan and manage agriculture fields. Water companies and universities can use this book to develop agricultural and meteorological sciences. The details of the modeling process are explained in this book for modelers.Also this book introduces new and advanced models for predicting hydrological variables. Predicting hydrological variables help water resource planning and management. These models can monitor droughts to avoid water shortage. And this contents can be related to SDG6, clean water and sanitation.The book explains how modelers use evolutionary algorithms to develop machine learning models. The book presents the uncertainty concept in the modeling process. New methods are presented for comparing machine learning models in this book. Models presented in this book can be applied in different fields. Effective strategies are presented for agricultural and water management. The models presented in the book can be applied worldwide and used in any region of the world. The models of the current books are new and advanced. Also, the new optimization algorithms of the current book can be used for solving different and complex problems. This book can be used as a comprehensive handbook in the agricultural and meteorological sciences. This book explains the different levels of the modeling process for scholars.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 208 pp. Englisch.

Application of Machine Learning Models in Agricultural and Meteorological Sciences
Ehteram, Mohammad; Seifi, Akram; Banadkooki, Fatemeh Barzegari
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND.