Entropy-Based Parameter Estimation in Hydrology:
Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spect...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Dordrecht
Springer Netherlands
1998
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Schriftenreihe: | Water Science and Technology Library
30 |
Schlagworte: | |
Online-Zugang: | BTU01 URL des Erstveröffentlichers |
Zusammenfassung: | Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution |
Beschreibung: | 1 Online-Ressource (XV, 368 p) |
ISBN: | 9789401714310 |
DOI: | 10.1007/978-94-017-1431-0 |
Internformat
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520 | |a Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution | ||
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Datensatz im Suchindex
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any_adam_object | |
author | Singh, Vijay P. |
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author_role | aut |
author_sort | Singh, Vijay P. |
author_variant | v p s vp vps |
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bvnumber | BV045176621 |
collection | ZDB-2-EES |
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dewey-search | 551.4 |
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dewey-tens | 550 - Earth sciences |
discipline | Geologie / Paläontologie |
doi_str_mv | 10.1007/978-94-017-1431-0 |
format | Electronic eBook |
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spelling | Singh, Vijay P. Verfasser aut Entropy-Based Parameter Estimation in Hydrology by Vijay P. Singh Dordrecht Springer Netherlands 1998 1 Online-Ressource (XV, 368 p) txt rdacontent c rdamedia cr rdacarrier Water Science and Technology Library 30 Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution Earth Sciences Hydrogeology Geoengineering, Foundations, Hydraulics Atmospheric Sciences Earth sciences Atmospheric sciences Engineering geology Engineering / Geology Foundations Hydraulics Hydrologie (DE-588)4026309-5 gnd rswk-swf Parameterschätzung (DE-588)4044614-1 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Parameterschätzung (DE-588)4044614-1 s Hydrologie (DE-588)4026309-5 s 2\p DE-604 Erscheint auch als Druck-Ausgabe 9789048150892 https://doi.org/10.1007/978-94-017-1431-0 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Singh, Vijay P. Entropy-Based Parameter Estimation in Hydrology Earth Sciences Hydrogeology Geoengineering, Foundations, Hydraulics Atmospheric Sciences Earth sciences Atmospheric sciences Engineering geology Engineering / Geology Foundations Hydraulics Hydrologie (DE-588)4026309-5 gnd Parameterschätzung (DE-588)4044614-1 gnd |
subject_GND | (DE-588)4026309-5 (DE-588)4044614-1 (DE-588)4143413-4 |
title | Entropy-Based Parameter Estimation in Hydrology |
title_auth | Entropy-Based Parameter Estimation in Hydrology |
title_exact_search | Entropy-Based Parameter Estimation in Hydrology |
title_full | Entropy-Based Parameter Estimation in Hydrology by Vijay P. Singh |
title_fullStr | Entropy-Based Parameter Estimation in Hydrology by Vijay P. Singh |
title_full_unstemmed | Entropy-Based Parameter Estimation in Hydrology by Vijay P. Singh |
title_short | Entropy-Based Parameter Estimation in Hydrology |
title_sort | entropy based parameter estimation in hydrology |
topic | Earth Sciences Hydrogeology Geoengineering, Foundations, Hydraulics Atmospheric Sciences Earth sciences Atmospheric sciences Engineering geology Engineering / Geology Foundations Hydraulics Hydrologie (DE-588)4026309-5 gnd Parameterschätzung (DE-588)4044614-1 gnd |
topic_facet | Earth Sciences Hydrogeology Geoengineering, Foundations, Hydraulics Atmospheric Sciences Earth sciences Atmospheric sciences Engineering geology Engineering / Geology Foundations Hydraulics Hydrologie Parameterschätzung Aufsatzsammlung |
url | https://doi.org/10.1007/978-94-017-1431-0 |
work_keys_str_mv | AT singhvijayp entropybasedparameterestimationinhydrology |