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Record Nr. |
UNINA9910682564603321 |
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Autore |
Ehteram Mohammad |
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Titolo |
Application of machine learning models in agricultural and meteorological sciences / / Mohammad Ehteram, Akram Seifi, and Fatemeh Barzegari Banadkooki |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore Pte Ltd., , [2022] |
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©2022 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (201 pages) |
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Disciplina |
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Soggetti |
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Artificial intelligence - Agricultural applications |
Machine learning |
Meteorology |
Aprenentatge automàtic |
Intel·ligència artificial |
Agricultura |
Meteorologia |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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The importance of agricultural and meteorological predictions -- Structure of Particle swarm optimization -- Structure of Shark optimization algorithm -- structure of sunflower optimization algorithm -- Structure of Henry gas solubility optimizer. |
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Sommario/riassunto |
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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. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and |
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