Application of Machine Learning Models in Agricultural and Meteorological Sciences

Ehteram, Mohammad, Seifi, Akram, Banadkooki, Fatemeh Barzegari

Application of Machine Learning Models in Agricultural and Meteorological Sciences
  • 出版商: Springer
  • 出版日期: 2024-03-23
  • 售價: $6,380
  • 貴賓價: 9.5 折 $6,061
  • 語言: 英文
  • 頁數: 196
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9811997357
  • ISBN-13: 9789811997358
  • 相關分類: Machine Learning

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

本書是一本全面的農業與氣象預測指南。它展示了用於預測目標變數的先進模型。本書解釋了建模過程中的不同細節和概念。本書中的模型有助於改善農業和灌溉管理，對氣象組織也具有重要價值。

本書的先進模型能夠準確估算氣象和農業變數。建模者、研究人員、農民、學生和學者可以利用新的優化演算法和進化機器學習來更好地規劃和管理農田。水務公司和大學可以利用本書來發展農業和氣象科學。本書詳細解釋了建模過程，供建模者參考。

此外，本書還介紹了用於預測水文變數的新型先進模型。預測水文變數有助於水資源的規劃和管理。這些模型可以監測乾旱，以避免水資源短缺。這些內容與可持續發展目標6（SDG6），即清潔水和衛生有關。

本書解釋了建模者如何使用進化演算法來開發機器學習模型，並在建模過程中介紹了不確定性概念。本書提出了比較機器學習模型的新方法。書中展示的模型可以應用於不同領域，並提出了有效的農業和水資源管理策略。書中所呈現的模型可在全球範圍內應用，適用於世界任何地區。本書中的模型是新型且先進的，此外，本書的新優化演算法可用於解決各種複雜問題。本書可作為農業和氣象科學的綜合手冊，並解釋了建模過程的不同層次，供學者參考。

作者簡介

Mohammad Ehtearm is a researcher in artificial intelligence. He has a Ph.D. in Computer Science and a Ph.D. in Civil Engineering. His previous positions include a visiting and post-doctoral researcher at university of different universities of Canada, USA, and Poland, a manager of dam and irrigation project, manager of rehabilitation of dam and expert of stability, monitoring, and operation of dams in Isfahan Regional Water (2014-2016), a lecturer in Islamic Azad University, Kashan, Iran (2016-2018), and a manager of different projects of artificial intelligence of Iran including finding optimal location of mines and grade estimation of raw materials. His research interests generally lie in the areas application of remote sensing in water resources, water, energy, and food nexus, sustainable water resources development, extreme hydrological events, river engineering, remote sensing in water resources, dam and hydropower operation, geotechnical engineering, mining engineering, and artificial intelligence, and remote sensing in mining engineering.

Akram Seifi is an associate professor at Water and Science Engineering Department of Vali-e-Asr University of Rafsanjan, Iran, with broad research interests in environmental science, water quality, and drip irrigation management, with a particular focus on artificial intelligence modeling. She holds a Ph.D. and M.Sc. degrees on Irrigation and Drainage Engineering from the Tarbiat Modares University, Tehran.

Fatemeh Barzegari Banadkooki is an assistant professor at Agricultural Department, Payame Noor University, Tehran, Iran, with broad research interests in environmental science, water quality, and water resource management, with a particular focus on artificial intelligence modeling. She holds a Ph.D. on Watershed Management Science from the Yazd University, Yazd.

作者簡介(中文翻譯)

Mohammad Ehtearm 是一位人工智慧研究者。他擁有計算機科學和土木工程的博士學位。他的過去職位包括在加拿大、美國和波蘭不同大學的訪問學者和博士後研究員，擔任水壩和灌溉項目的經理，伊斯法罕地區水務公司水壩穩定性、監測和運營的專家（2014-2016），伊朗卡尚伊斯蘭阿茲哈大學的講師（2016-2018），以及負責伊朗不同人工智慧項目的經理，包括尋找礦場的最佳位置和原材料的品級估算。他的研究興趣主要集中在遙感在水資源中的應用、水、能源和食品的聯結、可持續水資源發展、極端水文事件、河流工程、遙感在水資源中的應用、水壩和水電運營、岩土工程、礦業工程、人工智慧以及遙感在礦業工程中的應用等領域。

Akram Seifi 是伊朗拉夫桑詹瓦利·阿斯爾大學水與科學工程系的副教授，研究興趣廣泛，涵蓋環境科學、水質和滴灌管理，特別專注於人工智慧建模。她擁有德黑蘭塔爾比亞特·莫達雷斯大學的灌溉與排水工程博士和碩士學位。

Fatemeh Barzegari Banadkooki 是伊朗德黑蘭的佩亞梅·努爾大學農業系的助理教授，研究興趣廣泛，涵蓋環境科學、水質和水資源管理，特別專注於人工智慧建模。她擁有雅茲大學的流域管理科學博士學位。

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