By Vijay P. Singh (auth.)
Since the pioneering paintings of Shannon within the overdue 1940's at the improvement of the speculation of entropy and the landmark contributions of Jaynes a decade later resulting in the improvement of the main of utmost entropy (POME), the idea that of entropy has been more and more utilized in a large spectrum of components, together with chemistry, electronics and communications engineering, facts acquisition and garage and retreival, information tracking community layout, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, photograph processing, administration sciences, operations study, trend popularity and identity, photogrammetry, psychology, physics and quantum mechanics, reliability research, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so forth. New components discovering program of entropy have on the grounds that persevered to spread. The entropy inspiration is certainly flexible and its applicability common. within the region of hydrology and water assets, various functions of entropy were said in the past 3 a long time or so. This booklet specializes in parameter estimation utilizing entropy for a few distributions usually utilized in hydrology. within the entropy-based parameter estimation the distribution parameters are expressed when it comes to the given info, known as constraints. hence, the tactic lends itself to a actual interpretation of the parameters. as the info to be unique often constitutes adequate information for the distribution into account, the entropy process presents a quantitative method to convey the data inside the distribution.
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Extra resources for Entropy-Based Parameter Estimation in Hydrology
Linear routing of lateral inflow in uniform open channels. Eng. Sc. Thesis, University College, Cork, Ireland. N. , 1984. Fitting the SB curve by the method of maximum likelihood. Journal of Hydrology, Vol. 67, pp. 67-75. , 1994. Frequency analysis of upper Cauvert flood data by Lmoments. Water Resources Management, Vol. 8, pp. 183-201. R. , 1997. Regional frequency analysis of Wabash River flood data by L-moments. Journal of Hydrologic Engineering, Vol. 4, pp. 169-179. , 1987. An investigation of the instrumental varaible-approximate maximum likelihood method of modeling and forecasting daily flows.
Thus, there is a close link between equilibrium and uniform distribution and then between maximum entropy (uniform distribution) and minimum rate of energy dissipation. This link plays a fundamental role in river engineering and training works, river morphology, evolution of deltas, etc. 2) By definition f(x) is a rectangular pulse of length (b-a) and height l/(b-a). The cumulative distribution function (cdf) of the uniform distribution can be expressed as x-a F(x)=b-a V. P. 3) 46 The uniform distribution does not have any parameter, for once one bound is known the other bound is fixed by virtue of the rectangularity of the distribution.
Estimation for the three-parameter Weibull, lognormal, and gamma distributions. Computational Statistics and Data Analysis, Vol. 1, pp. 11-23. Kitanidis, P. , 1986. Parameter uncertainty in estimation of spatial functions: Bayesian analysis. Water Resources Research, Vol. 4, pp. 499-507. K. , 1985. Maximum likelihood parameter estimation of hydrologic spatial processes by the Gauss-Newton method. Journal o/Hydrology, Vol. 79, pp. 53-71. E. , 1990. Maximum likelihood estimation for shifted Weull and lognormal distributions.
Entropy-Based Parameter Estimation in Hydrology by Vijay P. Singh (auth.)