A New Parallel Optimization Algorithm for Parameter Identification in Ordinary Differential Equations
Abstract
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1988
- Accession Number
- ADA455254
Entities
People
- J. E. Dennis Jr.
- Karen A. Williamson
Organizations
- Rice University