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.

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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

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Algorithms
  • Applied Mathematics
  • Differential Equations
  • Equations
  • Equations Of State
  • Evolutionary Algorithms
  • Heuristic Methods
  • Identification
  • Information Operations
  • Mathematical Analysis
  • Mathematics
  • Optimization
  • Real Variables
  • Scientific Research

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Statistical inference.