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Engineering Commons

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Theses/Dissertations

1995

Engineering Management & Systems Engineering Theses & Dissertations

Industrial Engineering

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Full-Text Articles in Engineering

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 Jan 1995

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 ...


A Nonlinear Dynamic Method For Supporting Large-Scale Decision-Making In Uncertain Environments, Wayne Woodhams Jan 1995

A Nonlinear Dynamic Method For Supporting Large-Scale Decision-Making In Uncertain Environments, Wayne Woodhams

Engineering Management & Systems Engineering Theses & Dissertations

This research developed a methodology for supporting decision making by reducing uncertainty in decision environments which are too large, dynamic and complex to be treated by traditional quantitative and simulation techniques. These environments are complex because of the free choice associated with human involvement, and the existence of a large number of interrelated factors which influence the outcomes of the decision process. They are dynamic because the ground rules affecting those interrelationships are constantly changing. Uncertainty cannot be treated probabilistically, since identification of a full set of outcomes and factors of influence is not possible.

The venue for the investigation ...