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Computer‐generated multicomponent calibration designs for optimal analysis sample predictions
Author(s) -
Hitchcock Kimberly,
Kalivas John H.,
Sutter Jon M.
Publication year - 1992
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180060206
Subject(s) - calibration , simulated annealing , sample size determination , computer science , sample (material) , basis (linear algebra) , optimal design , mathematical optimization , algorithm , variable (mathematics) , design of experiments , global optimization , mathematics , statistics , machine learning , chromatography , chemistry , mathematical analysis , geometry
This paper utilizes variable step size generalized simulated annealing (VSGSA) to design multicomponent calibration samples for spectroscopic data. VSGSA is an optimization procedure which is capable of converging to exact positions of global optima located on multidimensional continuous functions. On the basis of analysis sample response vectors, optimally designed calibration concentration matrices are obtained assuming knowledge of components present. The complexity of response surfaces established by the optimization criteria is described.