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Dynamic stochastic models from empirical data
Time-series analysis. Stochastic processes. Estimation theory. System analysis. --- Operations Research --- Mathematical Statistics --- Mathematics --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Physical Sciences & Mathematics --- Time-series analysis. --- Stochastic processes. --- Estimation theory. --- System analysis. --- Network theory --- Systems analysis --- Estimating techniques --- Random processes --- Analysis of time series --- System theory --- Mathematical optimization --- Least squares --- Mathematical statistics --- Stochastic processes --- Probabilities --- Autocorrelation (Statistics) --- Harmonic analysis --- Network analysis --- Network science
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Statistical science --- Stochastic processes --- Estimation theory. --- Stochastic processes. --- System analysis. --- Time-series analysis. --- Time-series analysis --- Estimation theory --- System Analysis --- System analysis --- 519.216 --- 519.2 --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- 519.216 Stochastic processes in general. Prediction theory. Stopping times. Martingales --- Stochastic processes in general. Prediction theory. Stopping times. Martingales --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization --- Random processes --- Estimating techniques --- Least squares
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Operational research. Game theory --- Mathematics --- Meteorology. Climatology --- Geology. Earth sciences --- Environmental protection. Environmental technology --- Engineering sciences. Technology --- hydrologie --- analyse (wiskunde) --- milieukunde --- stochastische analyse --- time series analysis --- wiskunde --- geografie --- ingenieurswetenschappen --- kansrekening --- klimaatverandering
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Mathematical statistics --- Statistical physics --- Geology. Earth sciences --- Engineering sciences. Technology --- Civil engineering. Building industry --- Environmental planning --- hydrologie --- patroonherkenning --- statistische kwaliteitscontrole --- factoranalyse --- industriële statistieken --- ruimtelijke ordening --- ingenieurswetenschappen
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The Hilbert-Huang Transform ((HHT) is a recently developed technique which is used to analyze nonstationary data. Hydrologic and environmental series are, in the main, analyzed by using techniques which were developed for stationary data. This has led to problems of interpretation of the results. Environmental and hydrologic series are quite often nonstationary. The basic objective of the material discussed in this book is to analyze these data by using methods based on the Hilbert-Huang transform. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests. Audience This book will be of value to researchers interested in climate change and advanced graduate students in civil engineering, atmospheric sciences and statistics.
Operational research. Game theory --- Mathematics --- Meteorology. Climatology --- Geology. Earth sciences --- Environmental protection. Environmental technology --- Engineering sciences. Technology --- hydrologie --- analyse (wiskunde) --- milieukunde --- stochastische analyse --- time series analysis --- wiskunde --- geografie --- ingenieurswetenschappen --- kansrekening --- klimaatverandering
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Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics. Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals. The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity. The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice. Audience This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students.
Mathematical statistics --- Statistical physics --- Geology. Earth sciences --- Engineering sciences. Technology --- Civil engineering. Building industry --- Environmental planning --- hydrologie --- patroonherkenning --- statistische kwaliteitscontrole --- factoranalyse --- industriële statistieken --- ruimtelijke ordening --- ingenieurswetenschappen
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