Search
Feedback
About UniCat 
Help
News
| Listing 1 - 10 of 24 | << page >> |
Sort by
|
Book
ISBN: 3319673408 3319673394 Year: 2018 Publisher: Cham : Springer International Publishing : Imprint: Springer,
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
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. .
Environment. --- Oceanography. --- Physical geography. --- Ecology. --- Statistics. --- Climate change. --- Climate Change. --- Physical Geography. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Climatology --- Multivariate analysis. --- Time-series analysis. --- Statistical methods. --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Matrices --- Climatic changes. --- Balance of nature --- Biology --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Environmental sciences --- Population biology --- Oceanography, Physical --- Oceanology --- Physical oceanography --- Thalassography --- Earth sciences --- Marine sciences --- Ocean --- Geography --- Changes, Climatic --- Changes in climate --- Climate change --- Climate change science --- Climate changes --- Climate variations --- Climatic change --- Climatic changes --- Climatic fluctuations --- Climatic variations --- Global climate changes --- Global climatic changes --- Climate change mitigation --- Teleconnections (Climatology) --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Ecology --- Environmental aspects --- Ecology . --- Statistics . --- Global environmental change
Book
ISBN: 3110424983 9783110424904 3110424908 9783110424911 3110424916 9783110424980 9783110430011 3110430010 Year: 2016 Publisher: Berlin Boston
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern quantitative tools and techniques designed specifically to meet the needs of environmental sciences and related fields. This book has an impressive coverage of the scope. Main techniques described in this book are models for linear and nonlinear environmental systems, statistical & numerical methods, data envelopment analysis, risk assessments and life cycle assessments. These state-of-the-art techniques have attracted significant attention over the past decades in environmental monitoring, modeling and decision making. Environmental Data Analysis explains carefully various data analysis procedures and techniques in a clear, concise, and straightforward language and is written in a self-contained way that is accessible to researchers and advanced students in science and engineering. This is an excellent reference for scientists and engineers who wish to analyze, interpret and model data from various sources, and is also an ideal graduate-level textbook for courses in environmental sciences and related fields. Contents:PrefaceTime series analysisChaos and dynamical systemsApproximationInterpolationStatistical methodsNumerical methodsOptimizationData envelopment analysisRisk assessmentsLife cycle assessmentsIndex
Environmental sciences --- Environmental science --- Science --- Data processing. --- Mathematics. --- Data Analysis. --- Environmental Science.
Book
ISBN: 9783658359294 Year: 2022 Publisher: Wiesbaden, Germany : Springer,
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
Systems biology. --- Computational biology --- Bioinformatics --- Biological systems --- Molecular biology
Book
ISBN: 9783111012681 9783111012919 Year: 2023 Publisher: Berlin Boston
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
With the dramatic development of air-space-ground-sea environmental monitoring networks and large-scale high-resolution Earth simulators, Environmental science is facing opportunities and challenges of big data. Environmental Data Analysis focuses on state-of-the-art models and methods for big environmental data and demonstrates their applications through various case studies in the real world. It covers the comprehensive range of topics in data analysis in space, time and spectral domains, including linear and nonlinear environmental systems, feature extraction models, data envelopment analysis, risk assessments, and life cycle assessments. The 2nd Edition adds emerging network models, including neural networks, complex networks, downscaling analysis and streaming data on network. This book is a concise and self-contained work with enormous amount of information. It is a must-read for environmental scientists who struggle to conduct big data mining and data scientists who try to find the way into environmental science.
Environmental sciences --- Data processing. --- Mathematics. --- Environmental science --- Science --- Data Analysis. --- Environmental Science.
Digital
ISBN: 9783319673400 Year: 2018 Publisher: Cham Springer International Publishing
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
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. .
Statistical science --- Hydrosphere --- Meteorology. Climatology --- General ecology and biosociology --- Physical geography --- time series analysis --- statistiek --- ecologie --- fysische geografie --- oceanografie --- klimaatverandering --- statistisch onderzoek
Digital
ISBN: 9783658359294 9783658359287 9783658359300 Year: 2022 Publisher: Wiesbaden Springer Fachmedien, Imprint: Springer Vieweg
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
Boolean control networks (BCNs) are a kind of parameter-free model, which can be used to approximate the qualitative behavior of biological systems. After converting into a model similar to the standard discrete-time state-space model, control-theoretic problems of BCNs can be studied. In control theory, state observers can provide state estimation for any other applications. Reconstructibility condition is necessary for the existence of state observers. In this thesis explicit and recursive methods have been developed for reconstructibility analysis. Then, an approach to design Luenberger-like observer has been proposed, which works in a two-step process (i.e. predict and update). If a BCN is reconstructible, then an accurate state estimate can be provided by the observer no later than the minimal reconstructibility index. For a wide range of applications the approach has been extended to enable design of unknown input observer, distributed observers and reduced-order observer. The performance of the observers has been evaluated thoroughly. Furthermore, methods for output tracking control and fault diagnosis of BCNs have been developed. Finally, the developed schemes are tested with numerical examples. About the author Zhihua Zhang received the B.Sc. degree and M.Sc. degree in electrical engineering from the TU Kaiserslautern, Germany, respectively, in 2013 and 2015. In 2021 he finished Ph.D. in the area of Boolean control networks.
Human biochemistry --- Biotechnology --- Computer science --- medische biochemie --- toegepaste informatica --- bio-engineering --- computers --- biotechnologie --- computerkunde
Digital
ISBN: 9783110424904 9783110424980 9783110430011 Year: 2016 Publisher: Berlin ;; Boston De Gruyter
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
Digital
ISBN: 9783111012681 9783111012919 9783111012544 Year: 2023 Publisher: Berlin ;; Boston De Gruyter
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
Book
ISBN: 0128187034 0128187042 9780128187043 9780128187036 Year: 2020 Publisher: Amsterdam Elsevier
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
"Provides a step-by-step guide for applying big data mining tools to climate and environmental research Presents a comprehensive review of theory and algorithms of big data mining for climate change Includes current research in climate and environmental science as it relates to using big data algorithms"--
Data mining. --- Climatology --- Statistical methods. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching
Multi
ISBN: 9780128187043 0128187042 0128187034 9780128187036 Year: 2020 Publisher: Amsterdam, Netherlands ; Oxford, England ; Cambridge, Massachusetts : Elsevier,
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
"Provides a step-by-step guide for applying big data mining tools to climate and environmental research Presents a comprehensive review of theory and algorithms of big data mining for climate change Includes current research in climate and environmental science as it relates to using big data algorithms"--
Information systems --- Data mining. --- Climatology --- Statistical methods.
| Listing 1 - 10 of 24 | << page >> |
Sort by
|