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Articles 61 - 65 of 65
Full-Text Articles in Operational Research
Multidimensional Approach To Implementation Of Continuous Process Improvement Utilizing Small Run Analysis In A Shipyard Environment, Paul Ray Hollandsworth
Multidimensional Approach To Implementation Of Continuous Process Improvement Utilizing Small Run Analysis In A Shipyard Environment, Paul Ray Hollandsworth
Engineering Management & Systems Engineering Theses & Dissertations
Nationally, both public and private shipyards are experiencing a high rework rate (over 40%) in the fabrication of plug connectors used for electronic systems onboard Navy vessels. The shipyard's survival depends on acquiring the elements necessary to maintain a major industry in a position of continuous improvement that produces a better product than their competitors, at less cost, in a safe manner, and on schedule.
This research addresses the complex problem of how to introduce quality control methodologies within a job shop environment that assists in identifying variables that influence the rework rate of plug fabrication process over a four …
Multilayer Perceptrons For Classification, Lisa M. Belue
Multilayer Perceptrons For Classification, Lisa M. Belue
Theses and Dissertations
Techniques for training, testing, and validating multilayer perceptrons are thoroughly examined. Results obtained using perceptrons are compared and contrasted with two multivariate discriminant analysis techniques- logistic regression and k neighbor. Methods for determining significant input features are investigated and a procedure for examining the confidence to place in the significance of these features is developed. Procedures to evaluate the applicability of high-order feature inputs are examined. These methods and procedures are applied to two very different applications. The first application concerns the prediction of Air Force pilot retention/separation rates for input to force projection models. The second application concerns the …
Transformation Of Combat Data In Support Of Battle Trace, Hyoung-Kyu Choi
Transformation Of Combat Data In Support Of Battle Trace, Hyoung-Kyu Choi
Theses and Dissertations
The purpose of this study was to find an appropriate way of characterizing battle data as a function of time. This study was initially designed to remove the numerical instability problem cited in Barr's battle trace methodology as suggested by TRAC-MTRY. The research focused on the instability problem and identifying/recommending a technique that improved the efficiency of computation, and enhanced an analyst's ability to meaningfully interpret the battle trace. Two Lanchester's Square Law based methodologies are introduced and analyzed. The results of this analysis indicate that the battle trace of a constant value generated by Lanchester's Square Law integration seemed …
Confidence Interval Estimation For Output Of Discrete-Event Simulations Using The Kalman Filter, Randall B. Howard
Confidence Interval Estimation For Output Of Discrete-Event Simulations Using The Kalman Filter, Randall B. Howard
Theses and Dissertations
Discrete-event simulation is computer modeling of stochastic, dynamic systems. The Kalman filter is a Bayesian stochastic estimation algorithm. Because of the correlated nature of simulation output, it is difficult to apply the methods of classical statistics directly when constructing confidence intervals of discrete-event simulation parameters. Through the determination of a dynamics equation and application of the Kalman filter to simulation output data, three new confidence interval construction techniques have been developed. One technique obtains an estimate of the mean value and its associated variance from an estimated Kalman filter. The second technique utilizes Multiple Model Adaptive Estimation (MMAE) techniques to …
A Sensitivity Analysis Of Circular Error Probable Approximation Techniques, Peter Puhek
A Sensitivity Analysis Of Circular Error Probable Approximation Techniques, Peter Puhek
Theses and Dissertations
Several algebraic CEP estimates models were examined in this study. Each assumes that the crossrange and downrange miss distances of the sample data follow a bivariate normal distribution. The analysis determined the sensitivities of these models to changes in the parameters of sample size, bias, correlation, and ellipticity. The accuracy of each model is expressed in terms of relative error, and the parameter regions in which a certain method dominated as the most accurate were noted. In general, it was found that bias was the most significant parameter in determining the best CEP method. A simple method, based on the …