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• W1540941301 abstract "In this paper we present a study on parameter estimation in the field of resin production. The mathematical model of the chemical process contains a set of 12 differential algebraic equations (DAEs) and 16 unknown parameters; 8 series of measurements are available, performed under different initial conditions and different temperatures. In order to estimate the unknown parameters we solve the system of model equations and tune the model by varying the parameters in order to fit the solution of the DAEs with the measurements. The differential equations are solved by the BDF method. For the fitness criterion we use a (weighted) least squares sum, which is minimised by a Levenberg- Marquardt algorithm. Not only the optimal parameters are determined, but also their reliability and the feasibility of the mathematical model. It can be decided that 4 of the 16 parameters cannot be determined from the data given." @default.
• W1540941301 created "2016-06-24" @default.
• W1540941301 creator A5083845202 @default.
• W1540941301 date "1996-01-01" @default.
• W1540941301 modified "2023-09-26" @default.
• W1540941301 title "Parameter Estimation in Chemical Engineering, a case study for resin production" @default.
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• W1540941301 doi "https://doi.org/10.1007/978-3-642-80149-5_27" @default.
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