Auteur : Noratiqah Mohd. Ariff
la langue : ms
Éditeur:
Date de sortie : 2009
Auteur : J. R. M. Hosking
la langue : en
Éditeur: Cambridge University Press
Date de sortie : 2005-09-08
This book is the first complete account of the L-moment approach to regional frequency analysis of environmental extremes.
Auteur : Vijay Singh
la langue : en
Éditeur: Springer Science & Business Media
Date de sortie : 2013-04-17
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.
Auteur : A.R. Rao
la langue : en
Éditeur: Springer Science & Business Media
Date de sortie : 2008-04-18
Clustering techniques are used to identify groups of watersheds which have similar flood characteristics. This book, the first of its kind, is a comprehensive reference on how to use these techniques for regional flood frequency analysis. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory. It also brings together formerly scattered research findings on the application of clustering techniques to RFFA.
Auteur : P. P. Mujumdar
la langue : en
Éditeur: Cambridge University Press
Date de sortie : 2012-11-22
Provides unique synthesis of various modeling methodologies used to aid planning and operational decision making, for academic researchers and professionals.
Auteur : Manfred Mudelsee
la langue : en
Éditeur: Springer Science & Business Media
Date de sortie : 2010-08-26
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.