£108.75

Springer Machine Learning and Data Mining for Climate Science

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Description

Explore the emerging field of Climate Informatics through this comprehensive collection of research from the 4th International Workshop on Climate Informatics. Published by Springer, this book examines the application of data mining methods to climate science, providing a foundation for understanding complex climate systems. As the volume of data from satellites, environmental sensors, and climate models continues to grow, researchers need advanced tools to manage and interpret these massive datasets. This text offers insights into how machine learning and data mining can be used to monitor and measure environmental changes. It serves as a guide to the tools and methods required to navigate the modern landscape of climate data, helping researchers address the challenges posed by a changing climate through interdisciplinary approaches.

Key Features

Covers the fundamentals of Climate Informatics, a growing field combining data mining with climate science research.

Provides insights into using machine learning to process massive datasets from satellites and environmental sensors.

Explores methods for analyzing data produced by modern climate models to better understand the climate system.

Offers an interdisciplinary perspective on the tools and methods needed to address climate change challenges.

Presents research from the 4th International Workshop on Climate Informatics for current scientific perspectives.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
15 October 2016
Listed Since
07 October 2016

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