Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 93 for “"optimal decision"”.
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Structural Design as an Optimal Decision Process
Made available in DSpace on 2014-12-08T23:57:22Z (GMT). No. of bitstreams: 1 7013337.pdf: 5625693 bytes, checksum: 58330f64e030517e07f72e74886010a3 (MD5) Previous issue date: 1969
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Optimal Decision Making for Healthcare Operations: Models and Implementation
… support strategic, tactical, and operational decision making in healthcare systems. A large part of the thesis involves close collaborations with Hartford HealthCare (HHC), the largest hospital network in Connecticut, spanning seven hospitals with $5 billion annual revenue. In Chapter 2, we …
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A Simulated Annealing Approach to Designing Optimal Decision Trees for Classification, Prescriptive, and Survival Analysis
A binary decision tree is a highly interpretable machine learning model, as humans can easily understand how a prediction is made by answering a series of binary questions. Earlier work has provided a powerful framework for constructing optimal decision trees by utilizing multiple random warm …
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A model for the investigation of cost variances: the fuzzy set theory approach
… (fuzziness) surrounding the investigation decision. They are also based on the unrealistic assumptions of (1) a two-state system, and (2) constant level of accuracy and precision. In addition, the models suffer from the lack of applicability. They require precise numerical inputs to the …
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Consumer Learning and Brand Loyalty When Product Quality Is Unknown
… one aspect of which is the effect of learning on optimal decision making. This thesis explores the effects of consumer learning about product quality on a firm's optimal pricing strategies under different market structures.
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Near-Optimal Learning in Sequential Games
Decision making is ubiquitous, and some problems become particularly challenging due to their sequential nature, where later decisions depend on earlier ones. While humans have been attempting to solve sequential decision making problems for a long time, modern computational and machine learning …
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An Approach to Real Time Adaptive Decision Making in Dynamic Distributed Systems
… operation of a dynamic system requires (near) optimal real-time control decisions. Those decisions depend on a set of control parameters that change over time. Very often, the optimal decision can be made only with the knowledge of future values of control parameters. As a consequence, the …
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Stochastic optimization with decisions truncated by random variables and its applications in operations
We study stochastic optimization problems with decisions truncated by random variables and its applications in operations management. The technical difficulty of these problems is that the optimization problem is not convex due to the truncation. We develop a transformation technique to convert the …
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RESOURCE USE RATES: ESTIMATION OF TIME INVARIANT DECISION RULES (EROSION)
… has increased, understanding the soil management decision rule used by farmers has become more important. The model developed to analyze the optimal decision rule for soil use rates is essentially a supply response model which assumes rational expectations. It can be characterized as a dynamic …
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Optimal trees for prediction and prescription
For the past 30 years, decision tree methods have been one of the most widely-used approaches in machine learning across industry and academia, due in large part to their interpretability. However, this interpretability comes at a price--the performance of classical decision tree methods is …
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Large-Scale Algorithms for Machine Learning: Efficiency, Estimation Errors, and Beyond
… Chapters 5 and 6, we examine two algorithms for decision trees. Chapter 5 studies the computation of optimal decision trees, and introduces a new branch-and-bound method for optimal decision trees with general continuous features. Chapter 6 turns to the analysis of the CART algorithm under a …
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Optimal Estimation and Control Under Communication Network Constraints
Several new optimal estimation and control problems are introduced with hard constraints on the availability of information or on the number of times the information and/or control may be available. We are motivated by applications in networked control systems, but most of the results derived here …
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On the Co-Optimisation of Reserve Markets: With application to New Zealand
… These constraints also influence the optimal decision criteria for participants. A Supply Function Equilibrium model has been presented to investigate competition between suppliers located at either end of a reserve constrained transmission line. The optimal decision for these …
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Efficiently Learning Monotone Decision Trees with ID3
… My findings show that ID3 will produce an optimal decision tree for this class of Boolean functions.</p>
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Information Aggregation in Decision Markets under a Modified Hanson Market Maker
… market that allows subjects to make conscious decisions to infuence market outcomes, and thus it investigates the quality of the decisions made by the subjects as opposed to the accuracy of the market prices. Utilizing dispersed “not-state” information, we evaluate whether subjects can …
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Capacity control in network revenue management : clustering and risk-aversion
… revenue management is the practice of using optimal decision policies to increase revenues by controlling limited quantities of multiple resources' availability and prices over finite time. It is widely practiced in capacity-constrained service industries such as the airlines, hotels, car …
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Leveraging Gaussian Process Sampling for Sensitivity Analysis and Optimization in Engineering Design
… efficient sampling strategies, enabling informed decision-making under uncertainty by extracting information from a subset of potential functions for the model of interest. Despite their widespread use in machine learning and scientific computing, and the potential they hold for realizing …
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Designing hypothesis tests for digital image matching
… matching in its simplest form is a two class decision problem. Based on the evidence in two sensed images, a matching procedure must decide whether they represent two views of the same scene, or views of two different scens. Previous solutions to this problem were either based on an intuitive …
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A dynamic programming approach to single attribute process control
… The first model has fixed values of the decision variables and is optimized using the pattern search procedure. The second model is a dynamic formulation. The optimal decision policies developed using this model vary with the expected state of the process. Several cost components are …
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