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Articles 1 - 15 of 15
Full-Text Articles in Statistical Models
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Faculty Publications
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …
Statistical L-Moment And L-Moment Ratio Estimation And Their Applicability In Network Analysis, Timothy S. Anderson
Statistical L-Moment And L-Moment Ratio Estimation And Their Applicability In Network Analysis, Timothy S. Anderson
Theses and Dissertations
This research centers on finding the statistical moments, network measures, and statistical tests that are most sensitive to various node degradations for the Barabási-Albert, Erdös-Rényi, and Watts-Strogratz network models. Thirty-five different graph structures were simulated for each of the random graph generation algorithms, and sensitivity analysis was undertaken on three different network measures: degree, betweenness, and closeness. In an effort to find the statistical moments that are the most sensitive to degradation within each network, four traditional moments: mean, variance, skewness, and kurtosis as well as three non-traditional moments: L-variance, L-skewness, and L-kurtosis were examined. Each of these moments were …
Sample Size Requirements And Considerations For Models To Assess Human-Machine System Performance, Jennifer S. G. Lopez
Sample Size Requirements And Considerations For Models To Assess Human-Machine System Performance, Jennifer S. G. Lopez
Theses and Dissertations
Hierarchical Linear Models (HLMs), also known as multi-level models, are an extension of multiple regression analysis and can aid in the understanding of human and machine workloads of a system. These models allow for prediction and testing in systems with hierarchies of two or more levels. The complex interrelated variability of these multi-level models exists in operational settings, such as the Air Force Distributed Common Ground System Full Motion Video (AF DCGS FMV) community which is composed of individuals (Level-1), groups (Level-2), units (Level-3), and organizations (Level-4). Through the development of sample size requirements and considerations for multi-level models, this …
Analysis Of A Voting Method For Ranking Network Centrality Measures On A Node-Aligned Multiplex Network, Kyle S. Wilkinson
Analysis Of A Voting Method For Ranking Network Centrality Measures On A Node-Aligned Multiplex Network, Kyle S. Wilkinson
Theses and Dissertations
Identifying relevant actors using information gleaned from multiple networks is a key goal within the context of human aspects of military operations. The application of a voting theory methodology for determining nodes of critical importance—in ranked order of importance—for a node-aligned multiplex network is demonstrated. Both statistical and qualitative analyses on the differences of ranking outcomes under this methodology is provided. As a corollary, a multilayer network reduction algorithm is investigated within the context of the proposed ranking methodology. The application of the methodology detailed in this thesis will allow meaningful rankings of relevant actors to be produced on a …
Modeling Multimodal Failure Effects Of Complex Systems Using Polyweibull Distribution, Daniel A. Timme
Modeling Multimodal Failure Effects Of Complex Systems Using Polyweibull Distribution, Daniel A. Timme
Theses and Dissertations
The Department of Defense (DoD) enlists multiple complex systems across each of their departments. Between the aging systems going through an overhaul and emerging new systems, quality assurance to complete the mission and secure the nation‘s objectives is an absolute necessity. The U.S. Air Force‘s increased interest in Remotely Piloted Aircraft (RPA) and the Space Warfighting domain are current examples of complex systems that must maintain high reliability and sustainability in order to complete missions moving forward. DoD systems continue to grow in complexity with an increasing number of components and parts in more complex arrangements. Bathtub-shaped hazard functions arise …
Analysis And Modeling Of U.S. Army Recruiting Markets, Joshua L. Mcdonald
Analysis And Modeling Of U.S. Army Recruiting Markets, Joshua L. Mcdonald
Theses and Dissertations
The United States Army Recruiting Command (USAREC) is charged with finding, engaging, and ultimately enlisting young Americans for service as Soldiers in the U.S. Army. USAREC must decide how to allocate monthly enlistment goals, by aptitude and education level, across its 38 subordinate recruiting battalions in order to maximize the number of enlistment contracts produced each year. In our research, we model the production of enlistment contracts as a function of recruiting supply and demand factors which vary over the recruiting battalion areas of responsibility. Using county-level data for the period of recruiting year RY2010 through RY2013 mapped to recruiting …
Robust Sensitivity Analysis For The Joint Improvised Explosive Device Defeat Organization (Jieddo) Proposal Selection Model, Christina J. Willy
Robust Sensitivity Analysis For The Joint Improvised Explosive Device Defeat Organization (Jieddo) Proposal Selection Model, Christina J. Willy
Theses and Dissertations
Throughout Operations Iraqi Freedom and Enduring Freedom, the Department of Defense (DoD) faced challenges not experienced in our previous military operations. The enemy’s unwavering dedication to the use of improvised explosive devices (IEDs) against the coalition forces continues to challenge the day-to-day operations of the current war. The Joint Improvised Explosive Device Defeat Organization’s (JIEDDO) proposal solicitation process enables military and non-military organizations to request funding for the development of Counter-Improvised Explosive Device (C-IED) projects. Decision Analysis (DA) methodology serves as a tool to assist the decision maker (DM) in making an informed decision. This research applies Value Focused Thinking …
Using Agent-Based Modeling To Evaluate Uas Behaviors In A Target-Rich Environment, Joseph A. Van Kuiken
Using Agent-Based Modeling To Evaluate Uas Behaviors In A Target-Rich Environment, Joseph A. Van Kuiken
Theses and Dissertations
The trade-off between accuracy and speed is a re-occurring dilemma in many facets of military performance evaluation. This is an especially important issue in the world of ISR. One of the most progressive areas of ISR capabilities has been the utilization of Unmanned Aircraft Systems (UAS). Many people believe that the future of UAS lies in smaller vehicles flying in swarms. We use the agent-based System Effectiveness and Analysis Simulation (SEAS) to create a simulation environment where different configurations of UAS vehicles can process targets and provide output that allows us to gain insight into the benefits and drawbacks of …
Demonstration And Verification Of A Broad Spectrum Anomalous Dispersion Effects Tool For Index Of Refraction And Optical Turbulence Calculations, J. Jean Cohen
Theses and Dissertations
An atmospheric optical turbulence strength model with a broad wavelength range of 355nm (ultraviolet) to 8.6m (radio frequencies) has been created at AFIT and implemented into the High Energy Laser End-to-End Operational Simulation tool (HELEEOS). This modeling and simulation tool is a first principles atmospheric propagation and characterization model. Within HELEEOS lies the High-Resolution Transmission Molecular Absorption (HITRAN) database, containing 1,734,469 spectral lines for 37 different molecules as of version 12.0 (2004). HITRAN affords HELEEOS incredible accuracy for electromagnetic (EM) propagation prediction. A full understanding of optical turbulence is needed to successfully predict EM radiation propagation, particularly within the application …
Creating Multi Objective Value Functions From Non-Independent Values, Christopher D. Richards
Creating Multi Objective Value Functions From Non-Independent Values, Christopher D. Richards
Theses and Dissertations
Decisions are made every day and by everyone. As these decisions become more important, involve higher costs and affect a broader group of stakeholders it becomes essential to establish a more rigorous strategy than simply intuition or "going with your gut". In the past several decades, the concept of Value Focused Thinking (VFT) has gained much acclaim in assisting Decision Makers (DMs) in this very effort. By identifying and organizing what a DM values VFT is able to decompose the original problem and create a mathematical model to score and rank alternatives to be chosen. But what if the decision …
Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson
Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson
Theses and Dissertations
With increasing developments in computer technology and available software, simulation is becoming a widely used tool to model, analyze, and improve a real world system or process. However, simulation in itself is not an optimization approach. Common optimization procedures require either an explicit mathematical formulation or numerous function evaluations at improving iterative points. Mathematical formulation is generally impossible for problems where simulation is relevant, which are characteristically the types of problems that arise in practical applications. Further complicating matters is the variability in the simulation response which can cause problems in iterative techniques using the simulation model as a function …
Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard
Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard
Theses and Dissertations
This dissertation investigates a stochastic network formulation termed an event occurrence network (EON). EONs are graphical representations of the superposition of several terminating counting processes. An EON arc represents the occurrence of an event from a group of (sequential) events before the occurrence of events from other event groupings. Events between groups occur independently, but events within a group occur sequentially. A set of arcs leaving a node is a set of competing events, which are probabilistically resolved by order relations. An important EON metric is the probability of being at a particular node or set of nodes at time …
Groundwater Model Parameter Estimation Using Response Surface Methodology, Richard M. Cotman
Groundwater Model Parameter Estimation Using Response Surface Methodology, Richard M. Cotman
Theses and Dissertations
This thesis examined the use of response surface methodology (RSM) to estimate the parameters of a finite-element groundwater model. An existing two-dimensional, steady-state flow model of a fractured carbonate groundwater system in southwestern Ohio served as the calibration target data set. A Plackett-Burman screening design showed that only four of the ten hydraulic conductivity zones significantly contributed to the output of the finite-element model. Also, the effective porosity parameter did not significantly affect the model's output. Using only the four significant hydraulic conductivity parameters; four two-level, four-factor designed experiments were conducted to exploit the first-order response surface defined by a …
Estimating Groundwater Flow Parameters Using Response Surface Methodology, Leo C. Adams
Estimating Groundwater Flow Parameters Using Response Surface Methodology, Leo C. Adams
Theses and Dissertations
This thesis examined the use of response surface methodology RSM as a parameter estimation technique in the field of groundwater flow modeling. Using RSM, an attempt was made to calibrate three hydraulic parameters porosity, transverse permeability, and rate of recharge of an existing two- dimensional, steady-state flow model. The model simulated groundwater flow for a portion of landfill 10 located on Wright-Patterson Air Force Base, Ohio. The model had previously been calibrated by graphical matching observed water-levels to predicted water-levels. Using the parameter values from the earlier calibration effort as a starting point, a central composite design was developed and …
Developing Prediction Regions For A Time Series Model For Hurricane Forecasting, William Cheman
Developing Prediction Regions For A Time Series Model For Hurricane Forecasting, William Cheman
Theses and Dissertations
In this thesis, a class of time series models for forecasting a hurricanes future position based on its previous positions and a generalized model of hurricane motion are examined and extended. Results of a literature review suggest that meteorological models continue to increase in complexity while few statistical approaches, such as linear regression, have been successfully applied. An exception is provided by a certain class of time series models that appear to forecast storms almost as well as current meteorological models without their tremendous complexity. A suggestion for enhancing the performance of these time series models is pursued through an …