Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models
作者： Jene' D. Hendrickson , Soroosh Sorooshian , Larry E. Brazil
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摘要: An examination of the calibration aspect conceptual rainfall-runoff models was undertaken using Sacramento soil moisture accounting model and a study comparing performance Newton-type optimization algorithm with that direct search algorithm. Results indicate is more robust two because susceptible to poor conditioning response surface. Graphical studies surface model's parameter space confirmed presence discontinuities rough-textured surface, particularly in derivatives.
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