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An adaptive strategy for solving kinetic model concomitant estimation — Reduction problems
Author(s) -
Maria Gheorghe
Publication year - 1989
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450670514
Subject(s) - reduction (mathematics) , reliability (semiconductor) , nonlinear system , mathematical optimization , computer science , estimation theory , ridge , estimation , adaptive strategies , model order reduction , power (physics) , algorithm , mathematics , engineering , history , paleontology , physics , geometry , systems engineering , archaeology , quantum mechanics , biology , projection (relational algebra)
In order to simultaneously estimate the parameters and to reduce a complex kinetic model, an adaptive strategy which combines effective adaptive random search (ARS) and statistical ridge analysis steps is developed. As demonstrated, this strategy can save computational time because the estimation is not repeated with each reduced model. The use of ARS is preferred for highly nonlinear models and cases having multiple parameter constraints, guaranteeing reliability for interactively obtaining the global reduced model parameter solution.