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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.Â
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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R205
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