Multivariate Time Series Analysis in Climate and Environmental Research

Nonfiction, Science & Nature, Science, Earth Sciences, Geography, Biological Sciences, Environmental Science, Nature
Cover of the book Multivariate Time Series Analysis in Climate and Environmental Research by Zhihua Zhang, Springer International Publishing
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Author: Zhihua Zhang ISBN: 9783319673400
Publisher: Springer International Publishing Publication: November 9, 2017
Imprint: Springer Language: English
Author: Zhihua Zhang
ISBN: 9783319673400
Publisher: Springer International Publishing
Publication: November 9, 2017
Imprint: Springer
Language: English

This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation.

The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.  

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation.

The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.  

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