Application of Machine Learning Models in Agricultural and Meteorological Sciences

This book is a comprehensive guide for agricultural and meteorological predictions, presenting advanced models for predicting target variables. It helps better agriculture and irrigation management, and meteorological organizations can use it to develop agricultural and meteorological sciences. It also introduces new and advanced models for predicting hydrological variables, which can help water resource planning and management. The book explains how modelers use evolutionary algorithms to develop machine learning models and presents the uncertainty concept in the modeling process. Effective strategies are presented for agricultural and water management, and the models can be applied worldwide.

Format: Hardback
Length: 196 pages
Publication date: 22 March 2023
Publisher: Springer Verlag, Singapore

This comprehensive guide offers advanced models for agricultural and meteorological predictions, providing detailed explanations of the modeling process. It serves as a valuable resource for modelers, researchers, farmers, students, and scholars, enabling them to optimize agricultural fields and plan water resource management effectively. The book introduces new and advanced models for predicting hydrological variables, aiding in water resource planning and monitoring droughts to prevent water shortages. Its contents align with Sustainable Development Goal 6, focusing on clean water and sanitation. The book explains how evolutionary algorithms are used to develop machine learning models and introduces the concept of uncertainty in the modeling process. It presents methods for comparing machine learning models and showcases their applications in various fields, including agricultural and water management. These models are versatile and can be applied worldwide, making them a valuable tool for addressing global challenges.

Weight: 483g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811997327
Edition number: 1st ed. 2023