Parameter estimation with colored noise effect for differential hydrological grey model

Lee, Ru-huang; Wang, Ru-Yih

doi:10.1016/s0022-1694(98)00133-4

Cited by 25 publications

(10 citation statements)

References 7 publications

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“…In the 1990 s, many researchers studied the grey system theory and its applications. These include the grey relational analysis (Huang and Huang, 1996;Huang and Chu, 1999), the grey linear programming approach (Huang et al, 1992(Huang et al, , 1993(Huang et al, , 1994(Huang et al, , 1995, and the grey prediction theory Huang, 1996, 1997;Chen and Jou, 2000;Wang, 2002;Lee and Wang, 1998;Xia and Hu, 1997a). Recently, grey correlation evaluation methods and their applications have been developed by Xia and Hu (1997b); Xia (1995).…”

Section: Introductionmentioning

confidence: 99%

Change-point analysis of hydrological time series using grey relational method

Wong

et al. 2006

Journal of Hydrology

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Section: Introductionmentioning

confidence: 99%

Change-point analysis of hydrological time series using grey relational method

Wong

et al. 2006

Journal of Hydrology

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“…The SCE algorithm has been extensively used in hydrology (e.g. Duan et al 1992;Lee and Wang 1998;Hsieh and Wang 1999;Madsen 2003;Mertens et al 2004) and, in the case of RR models, it has also been proved to be superior to other global search techniques, such as the Multiple Start Simplex, Genetic Algorithms and Simulated Annealing (Gan and Bitfu 1996;Cooper et al 1997;Kuczera 1997;Franchini et al 1998). Some extensions to the main SCE algorithm have been proposed.…”

Section: Model Calibration Procedures Sce and Pest Optimisation Algormentioning

confidence: 99%

Parameter estimation in distributed hydrological modelling: comparison of global and local optimisation techniques

2007

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Much research has been spent in the last three decades in developing more effective and efficient automatic calibration procedures and in demonstrating their applicability to hydrological problems. Several problems have emerged when applying these procedures to calibration of conceptual rainfall -runoff and groundwater (GW) models, such as computational time, large number of calibration parameters, parameter identifiability, model response surface complexity, handling of multiple objectives and parameter equifinality. All these are expected to be much more severe for more complex models, for which comprehensive calibration studies have not so far been conducted. The scope of this paper is to investigate the performance of a global and a local optimisation technique, respectively, the Shuffled Complex Evolution algorithm and the gradientbased Gauss -Marquard -Levenberg algorithm, in calibration of physically based distributed models of different complexity. The models considered are a steady-state GW model, a transient GW model and a fully integrated model of the same catchment. The calibration is conducted in a multi-objective framework where two different aspects of the model response, the simulated runoff and the groundwater elevation are aggregated and simultaneously optimised. Different aggregated objective functions are used to give different weights to the calibration criteria. The results of the calibration procedures are compared in terms of effectiveness and efficiency and demonstrate the different performance of the methods. Moreover, a combination of the global and local techniques is investigated as an attempt to exploit the advantages of both procedures, while overcoming their drawbacks.

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“…The structure and behavior of DHGM(2,2) used in this investigation were taken from Lee and Wang (1998), and are presented again for convenience. The many grey characteristics of hydrosystems are such that grey system theory can be applied by treating the random process in a hydrosystem as a grey process.…”

Section: Redundant Wavelet Transformmentioning

confidence: 99%

“…The differential hydrological grey model with dual series, developed by Xia (1989a,b) and abbreviated as DHGM(2,2), is introduced to simulate the causal relationship between rainfall and runoff. Lee and Wang (1998) proposed the estimation of parameters given colored noise effect associated with DHGM(2,2). Model parameters are estimated by the least squares method with the colored noise effect, to improve the determination of parameters.…”

Section: Introductionmentioning

confidence: 99%

Applying multi-resolution analysis to differential hydrological grey models with dual series

Chou

2007

Journal of Hydrology

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Parameter estimation with colored noise effect for differential hydrological grey model

Cited by 25 publications

References 7 publications

Change-point analysis of hydrological time series using grey relational method

Change-point analysis of hydrological time series using grey relational method

Parameter estimation in distributed hydrological modelling: comparison of global and local optimisation techniques

Applying multi-resolution analysis to differential hydrological grey models with dual series

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