Entropy-Based Parameter Estimation in Hydrology

Nonfiction, Science & Nature, Science, Other Sciences, Meteorology, Earth Sciences
Cover of the book Entropy-Based Parameter Estimation in Hydrology by V.P. Singh, Springer Netherlands
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: V.P. Singh ISBN: 9789401714310
Publisher: Springer Netherlands Publication: April 17, 2013
Imprint: Springer Language: English
Author: V.P. Singh
ISBN: 9789401714310
Publisher: Springer Netherlands
Publication: April 17, 2013
Imprint: Springer
Language: English

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.

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

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.

More books from Springer Netherlands

Cover of the book Interactions of Energy and Climate by V.P. Singh
Cover of the book Trees of Life by V.P. Singh
Cover of the book Introduction to Aristotle’s Theory of Being as Being by V.P. Singh
Cover of the book Analytical Mechanics by V.P. Singh
Cover of the book Device Architecture and Materials for Organic Light-Emitting Devices by V.P. Singh
Cover of the book Mapping Equity and Quality in Mathematics Education by V.P. Singh
Cover of the book Agency and Integrality by V.P. Singh
Cover of the book Language Processing and Language Acquisition by V.P. Singh
Cover of the book Spatial Cognition by V.P. Singh
Cover of the book Polymer Science Dictionary by V.P. Singh
Cover of the book Diabetes Explained by V.P. Singh
Cover of the book Critical Survey of Studies on the Languages of Borneo by V.P. Singh
Cover of the book Space-Time Integration in Geography and GIScience by V.P. Singh
Cover of the book Recent Developments in Infant Nutrition by V.P. Singh
Cover of the book Intuition in Science and Mathematics by V.P. Singh
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy