A novel parameter estimation method for muskingum model using new Newton-type trust region algorithm

DOI10.1155/2014/634852zbMath1407.86023OpenAlexW2157305298WikidataQ59066743 ScholiaQ59066743MaRDI QIDQ1718809

Zhou Sheng, Li-Bin Liu, Aijia Ouyang, Gong Lin Yuan

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/634852

Mathematics Subject Classification ID

Point estimation (62F10) Hydrology, hydrography, oceanography (86A05) Geostatistics (86A32)

Related Items (5)

Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions ⋮ A class of parameter estimation methods for nonlinear Muskingum model using hybrid invasive weed optimization algorithm ⋮ Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions ⋮ An adaptive trust region algorithm for large-residual nonsmooth least squares problems ⋮ A modified HZ conjugate gradient algorithm without gradient Lipschitz continuous condition for non convex functions

Cites Work

• A hybrid of adjustable trust-region and nonmonotone algorithms for unconstrained optimization
• A new adaptive trust-region method for system of nonlinear equations
• A new genetic simulated annealing algorithm for flood routing model
• Generalized trapezoidal formulas for parabolic equations
• A New Algorithm for Unconstrained Optimization

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