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 Diagnosis of Mycotoxicoses by V.P. Singh
Cover of the book Product-Oriented Environmental Management Systems (POEMS) by V.P. Singh
Cover of the book Magnetic Resonance Imaging in Coronary Artery Disease by V.P. Singh
Cover of the book Immunity, Tumors and Aging: The Role of HSP70 by V.P. Singh
Cover of the book Studies in Recent Philosophy by V.P. Singh
Cover of the book Anticipating and Assessing Health Care Technology by V.P. Singh
Cover of the book Promoting, Assessing, Recognizing and Certifying Lifelong Learning by V.P. Singh
Cover of the book Conservation of the Biological Diversity as a Prerequisite for Sustainable Development in the Black Sea Region by V.P. Singh
Cover of the book Equality of Treatment and Trade Discrimination in International Law by V.P. Singh
Cover of the book Mathematics Education as a Research Domain: A Search for Identity by V.P. Singh
Cover of the book If Tropes by V.P. Singh
Cover of the book VLSI 2010 Annual Symposium by V.P. Singh
Cover of the book The Soils of Bangladesh by V.P. Singh
Cover of the book A Roadmap to the Successful Development and Commercialization of Microbial Pest Control Products for Control of Arthropods by V.P. Singh
Cover of the book Microbial Biochemistry 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