Stoch. dynamic predictions using kriging for nanoparticle synthesis

Event Details
  • Date/Time:
    • Tuesday April 28, 2009
      11:00 am - 12:00 pm
  • Location: Executive classroom
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    $0.00
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Contact
JC Lu
ISyE
Contact JC Lu
404-894-2300
Summaries

Summary Sentence: Stoch. dynamic predictions using kriging for nanoparticle synthesis

Full Summary: Stochastic dynamic predictions using kriging for nanoparticle synthesis

TITLE: Stochastic dynamic predictions using kriging for nanoparticle synthesis

SPEAKER: Professor Martha Grover

ABSTRACT:

Kriging is an empirical modeling approach that has been widely applied in engineering for the approximation of deterministic functions, due its flexibility and ability to interpolate observed data. Despite its statistical properties, kriging has not been developed to approximate stochastic functions or to describe the dynamics of systems with multiple outputs. Our paper proposes a methodology to construct approximate models for multivariate stochastic dynamic simulations using kriging, by combining ideas from design of experiments and dynamic systems modeling. We then apply the methodology in the prediction of a dynamic size distribution during the synthesis of nanoparticles.

Additional Information

In Campus Calendar
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Groups

H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Categories
Seminar/Lecture/Colloquium
Keywords
kriging
Status
  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 4:36pm
  • Last Updated: Oct 7, 2016 - 9:47pm