A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations

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1988-09
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Often in mathematical modeling, it is necessary to estimate numerical values for parameters occurring in a system of ordinary differential equations from experimental measurements of the solution trajectories. We will discuss some of the difficulties involved in the solution of this problem, and we will describe a new parallel quasi-Newton algorithm for finding values of the parameters so that the numerical solution of the state equation best fits the observed data in the weighted least squares sense.

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Technical report
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Dennis, J.E. Jr. and Williamson, Karen A.. "A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations." (1988) https://hdl.handle.net/1911/101648.

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