Studies on Time Series Applications in Environmental Sciences
Springer International Publishing (Verlag)
978-3-319-30434-2 (ISBN)
Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management.
In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code.
Hypotheses Testing on Meteorological Time Series.- Mathematical Methods Applied for Modeling Meteorological Time Series.- Models for Precipitation Series.- Modeling the Precipitation Evolution at Regional Scale.- Analysis and Models for Surface Water Quality.- Models for Pollutants Dissipation.- Spatial Interpolation with Applications.
"I enjoyed reading this carefully written book and would certainly recommend it to postgraduate students and researchers of meteorology, and applied mathematicians and statisticians who deal with such environmental science data." (Computing Reviews, October, 2017)
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | Intelligent Systems Reference Library |
| Zusatzinfo | XIII, 187 p. 86 illus., 24 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Naturwissenschaften ► Geowissenschaften ► Geologie | |
| Technik | |
| Schlagworte | artificial intelligence (incl. robotics) • Artificial Neural Networks • Atmospheric Forecasting • Box-Jenkins Methodology • computational Geosciences • Computational Intelligence • Engineering • Geophysical Modeling • Geostatistics • Geotechnical Engineering & Applied Earth Sciences • Geotechnical Engineering & Applied Earth Sciences • Intelligent Systems • support vector regression |
| ISBN-10 | 3-319-30434-8 / 3319304348 |
| ISBN-13 | 978-3-319-30434-2 / 9783319304342 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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