A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations
Dennis, J.E. Jr.
Williamson, Karen A.
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.
Citable link to this pagehttps://hdl.handle.net/1911/101648
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