Machine Learning and Data Mining Approaches to Climate Science Machine Learning and Data Mining Approaches to Climate Science

Machine Learning and Data Mining Approaches to Climate Science

Proceedings of the 4th International Workshop on Climate Informatics

    • $129.99
    • $129.99

Publisher Description

This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.

GENRE
Science & Nature
RELEASED
2015
June 30
LANGUAGE
EN
English
LENGTH
261
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
6.7
MB
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
2009
Computational Intelligence Techniques in Earth and Environmental Sciences Computational Intelligence Techniques in Earth and Environmental Sciences
2014
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
2021
geoENV VI – Geostatistics for Environmental Applications geoENV VI – Geostatistics for Environmental Applications
2008
Land Surface Observation, Modeling and Data Assimilation Land Surface Observation, Modeling and Data Assimilation
2013
Earth Systems Data Processing and Visualization Using MATLAB Earth Systems Data Processing and Visualization Using MATLAB
2019
Data Governance: The Definitive Guide Data Governance: The Definitive Guide
2021
Machine Learning Design Patterns Machine Learning Design Patterns
2020
Google BigQuery: The Definitive Guide Google BigQuery: The Definitive Guide
2019
Practical Machine Learning for Computer Vision Practical Machine Learning for Computer Vision
2021
Data Science on the Google Cloud Platform Data Science on the Google Cloud Platform
2022
Architecting Data and Machine Learning Platforms Architecting Data and Machine Learning Platforms
2023