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

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dc.contributor.authorDennis, J.E. Jr.en_US
dc.contributor.authorWilliamson, Karen A.en_US
dc.date.accessioned2018-06-18T17:28:17Zen_US
dc.date.available2018-06-18T17:28:17Zen_US
dc.date.issued1988-09en_US
dc.date.noteSeptember 1988en_US
dc.description.abstractOften 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.en_US
dc.format.extent17 ppen_US
dc.identifier.citationDennis, J.E. Jr. and Williamson, Karen A.. "A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations." (1988) <a href="https://hdl.handle.net/1911/101648">https://hdl.handle.net/1911/101648</a>.en_US
dc.identifier.digitalTR88-12en_US
dc.identifier.urihttps://hdl.handle.net/1911/101648en_US
dc.language.isoengen_US
dc.titleA New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equationsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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