A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations
RICE UNIV HOUSTON TX DEPT OF MATHEMATICAL SCIENCES
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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.
- Numerical Mathematics
- Physical Chemistry