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Comparison of function approximation, heuristic, and derivative‐based methods for automatic calibration of computationally expensive groundwater bioremediation models
Author(s) -
Mugunthan Pradeep,
Shoemaker Christine A.,
Regis Rommel G.
Publication year - 2005
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2005wr004134
Subject(s) - heuristic , calibration , mathematical optimization , benchmark (surveying) , function (biology) , approximation error , computer science , algorithm , mathematics , statistics , geology , geodesy , evolutionary biology , biology
The performance of function approximation (FA) methods is compared to heuristic and derivative‐based nonlinear optimization methods for automatic calibration of biokinetic parameters of a groundwater bioremediation model of chlorinated ethenes on a hypothetical and a real field case. For the hypothetical case, on the basis of 10 trials on two different objective functions, the FA methods had the lowest mean and smaller deviation of the objective function among all algorithms for a combined Nash‐Sutcliffe objective and among all but the derivative‐based algorithm for a total squared error objective. The best algorithms in the hypothetical case were applied to calibrate eight parameters to data obtained from a site in California. In three trials the FA methods outperformed heuristic and derivative‐based methods for both objective functions. This study indicates that function approximation methods could be a more efficient alternative to heuristic and derivative‐based methods for automatic calibration of computationally expensive bioremediation models.