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- W2110305691 abstract "Nonlinear Muskingum models are important tools in hydrological forecasting. In this paper, we have come up with a class of new discretization schemes including a parameter<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mrow><mml:mi>θ</mml:mi></mml:mrow></mml:math>to approximate the nonlinear Muskingum model based on general trapezoid formulas. The accuracy of these schemes is second order, if<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mi>θ</mml:mi><mml:mo>≠</mml:mo><mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:mrow></mml:math>, but interestingly when<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mi>θ</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:mrow></mml:math>, the accuracy of the presented scheme gets improved to third order. Then, the present schemes are transformed into an unconstrained optimization problem which can be solved by a hybrid invasive weed optimization (HIWO) algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the present methods. The numerical results substantiate the fact that the presented methods have better precision in estimating the parameters of nonlinear Muskingum models." @default.
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- W2110305691 date "2015-01-01" @default.
- W2110305691 modified "2023-10-16" @default.
- W2110305691 title "A Class of Parameter Estimation Methods for Nonlinear Muskingum Model Using Hybrid Invasive Weed Optimization Algorithm" @default.
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