Monday, May 20
1:30-3:30 PM
Salon B

MS9
Parameter Estimation and Optimum Experimental Design

Mathematical models for reallife processes typically contain parameters that have to be determined by experiment. The speakers will examine two issues related to this process: The design of experiments that produce highquality data for parameter estimation ("optimum experimental design") and the task of actually estimating the parameters from given experimental data ("parameter estimation"). Their presentations describe recent developments in numerical methods for the treatment of complex nonlinear models, especially DAE and PDE boundary value problems. They will discuss reduced GaussNewton and SQPtype methods, stepsize strategies, exploitation of structures, parallel algorithms, and applications from chemical engineering, mechanical engineering and environmental physics.

Organizers: Johannes P. Schloder, Universitat of Heidelberg, Germany; and
Stephen J. Wright, Argonne National Laboratory

Feasible Point Trust-Region Methods for Equality Constrained Least Squares Problems and Application to Parameter Estimation in Nonlinear Models with Singularities
Hubert Schwetlick and Stefan Schleiff, Technische Universitat Dresden, Germany
Global Optimization of Functionals Constrained by Differential Equations: Bayesian Search on Approximants
Prasana Venkatesh, University of Minnesota, Minneapolis
Optimum Experimental Design for Nonlinear Dynamic Processes: Methods, Algorithms, Applications in Robotics and Chemical Kinetics
Klaus-Dieter Hilf, Universitat Heidelberg, Germany
Efficient Numerical Methods for Parameter Estimation in Nonlinear 2D Transport Reaction Processes
Matthias Ziesse, Universitat Heidelberg, Germany

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LMH, 3/15/96