Imputation Methods for Missing Hydrometeorological Data Estimation

This book serves as a unique reference that provides a comprehensive discussion about the state-of-the-art spatial and temporal, statistical, and data mining methods for imputation of missing hydrometeorological data. The primary audience for this book are researchers, scientists, graduate-level and...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Teegavarapu, Ramesh S.V (مؤلف)
مؤلف مشترك: SpringerLink (Online service)
التنسيق: الكتروني كتاب الكتروني
اللغة:الإنجليزية
منشور في: Cham : Springer International Publishing : Imprint: Springer, 2024.
الطبعة:1st ed. 2024.
سلاسل:Water Science and Technology Library, 108
الموضوعات:
الوصول للمادة أونلاين:https://doi.org/10.1007/978-3-031-60946-6
الوسوم: إضافة وسم
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الوصف
الملخص:This book serves as a unique reference that provides a comprehensive discussion about the state-of-the-art spatial and temporal, statistical, and data mining methods for imputation of missing hydrometeorological data. The primary audience for this book are researchers, scientists, graduate-level and higher students, modelers, data scientists working in hydrological, meteorological, climatological, and earth sciences. Data analysts in other disciplines will also be interested in this book. The book appeals to graduate students, researchers in civil and environmental engineering, geosciences, climatology, and hydrological and data sciences. It will be an ideal reference book for state and federal agencies that collect and process hydrometeorological and climatological data. Engineering professionals, hydrologists, meteorologists, and data and spatial analysts dealing with large hydrometeorological datasets. Researchers and modelers involve in the development of long-term datasets at national and international institutions. .
وصف مادي:XVII, 517 p. 292 illus., 22 illus. in color. online resource.
ردمك:9783031609466
تدمد:1872-4663 ;
DOI:10.1007/978-3-031-60946-6