(Q58393632)

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Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models

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Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models (English)

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1 reference

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Soroosh Sorooshian

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author name string

Jene' D. Hendrickson

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1

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Larry E. Brazil

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3

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publication date

May 1988

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published in

Water Resources Research

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volume

24

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issue

5

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page(s)

691-700

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cites work

A Rapidly Convergent Descent Method for Minimization

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21 January 2018

The Automatic Calibration of Conceptual Catchment Models Using Derivative-Based Optimization Algorithms

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21 January 2018

River flow forecasting through conceptual models part I — A discussion of principles

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21 January 2018

A Simplex Method for Function Minimization

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21 January 2018

An Automatic Method for Finding the Greatest or Least Value of a Function

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21 January 2018

Surface water hydrology: On-line estimation

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21 January 2018

Stochastic parameter estimation procedures for hydrologie rainfall-runoff models: Correlated and heteroscedastic error cases

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21 January 2018

Automatic calibration of conceptual rainfall-runoff models: The question of parameter observability and uniqueness

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https://api.crossref.org/works/10.1029%2FWR024I005P00691

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21 January 2018

Evaluation of Maximum Likelihood Parameter estimation techniques for conceptual rainfall-runoff models: Influence of calibration data variability and length on model credibility

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https://api.crossref.org/works/10.1029%2FWR024I005P00691

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21 January 2018

`` Direct Search'' Solution of Numerical and Statistical Problems

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7 January 2021

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A method for the solution of certain non-linear problems in least squares

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7 January 2021

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10.1029/WR024I005P00691

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(Q58393632)

Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models

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