Operations Research, Systems Engineering and Industrial Engineering Commons^™

Knowledge Acquisition And Structuring By Multiple Experts In A Group Support Systems Environment, Bernard Lee Lewis

Engineering Management & Systems Engineering Theses & Dissertations

This study addresses the impact of Group Decision Support Systems (GDSS) on expert system development by multiple Domain Experts. Current approaches to building expert systems rely heavily on knowledge acquisition and prototyping by a Knowledge Engineer working directly with the Domain Expert. Although the complexity of knowledge domains and new organizational approaches demand the involvement of multiple experts, standard procedures limit the ability of the Knowledge Engineer to work with more than one expert at a time.

Group Decision Support Systems offer a networked computerized environment for group work activities, in which multiple experts may express their ideas concurrently and …

The Effect Of Repeatedly Sampling An Embedded Metamodel On The Simulation Response, John Kent Patterson

Theses and Dissertations

This study investigated the effect on simulation output of repeatedly sampling an embedded metamodel. A metamodel is said to be embedded within a simulation if it is used to replace a submodule of that simulation. Replacing a deterministic module with an embedded deterministic metamodel poses no apparent mathematical problems. However, using a deterministic metamodel to replace a stochastic simulation component could require additional corrective actions. This research was performed in two phases. The first phase dealt with a set of tandem queues. It was shown that as each queue was sequentially replaced with a metamodel, the total system variance was …

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …