Welcome to the Library Catalog of "Dunarea de Jos" University of Galati

Imputation Methods for Missing Hydrometeorological Data Estimation [electronic resource] / by Ramesh S.V. Teegavarapu.

By: Contributor(s): Material type: TextSeries: Water Science and Technology Library ; 108Publisher: Cham : Springer International Publishing : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XVII, 517 p. 292 illus., 22 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031609466
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • GB651-2998
Online resources:
Contents:
Introduction to Missing Data -- Methods for Imputation of Missing Data -- Temporal Interpolation Methods -- Spatial Interpolation Methods -- Data Driven Modes for Imputation -- Multiple Imputation Methods -- Evaluation of Methods and Imputed Data.
In: Springer Nature eBookSummary: 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. .
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Introduction to Missing Data -- Methods for Imputation of Missing Data -- Temporal Interpolation Methods -- Spatial Interpolation Methods -- Data Driven Modes for Imputation -- Multiple Imputation Methods -- Evaluation of Methods and Imputed Data.

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. .

There are no comments on this title.

to post a comment.
Biblioteca Universității "Dunărea de Jos" din Galați