Date of Award:

5-1994

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Mathematics and Statistics

Advisor/Chair:

Kevin Hestir

Abstract

A common problem in science and engineering applications deals with finding information about a system where only limited information is known. One example of this problem is determining the geometry of an aquifer or oil reservoir based on well tests taken at the site. The Conditional Coding Method attacks this type of problem. This method uses the Simulated Annealing Algorithm in conjunction with a probability model which generates possible solutions based on a uniform random number list. The Annealing Algorithm generates a conditional probability distribution on all possible solutions generated by the probability model, conditioned on the observed data set. The problem is attacked by sampling from this distribution. This method accounts for the noise inherent in the data set as well as the uncertainty due to the limited amount of data available.

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Included in

Mathematics Commons

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