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portada Application of Machine Learning Models in Agricultural and Meteorological Sciences
Type
Physical Book
Publisher
Language
Inglés
Pages
196
Format
Hardcover
Dimensions
23.4 x 15.6 x 1.3 cm
Weight
0.47 kg.
ISBN13
9789811997327

Application of Machine Learning Models in Agricultural and Meteorological Sciences

Mohammad Ehteram (Author) · Akram Seifi (Author) · Fatemeh Barzegari Banadkooki (Author) · Springer · Hardcover

Application of Machine Learning Models in Agricultural and Meteorological Sciences - Ehteram, Mohammad ; Seifi, Akram ; Banadkooki, Fatemeh Barzegari

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£ 186.35

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Wednesday, July 24 and Wednesday, July 31.
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Synopsis "Application of Machine Learning Models in Agricultural and Meteorological Sciences"

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.

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The book is written in English.
The binding of this edition is Hardcover.

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