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 32 for “"black box model"”.
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Scalable black-box model explainability through low-dimensional visualizations
… to provide visual intuitive explanations for how black-box models work. The first is a projection pursuit-based method that seeks to provide data-point specific explanations. The second is a generalized additive model approach that seeks to explain the model on a more holistic level, enabling …
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Prediction interval modeling using Gaussian process quantile regression
… to construct prediction intervals for a generic black-box point forecast model is presented. The prediction intervals are learned from the forecasts of the black-box model and the actual realizations of the forecasted variable by using quantile regression on the observed prediction error …
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Black-box printer models and their applications
… to as dot-gain, is complicated. The printer models which are developed according to a pre-designed test page can either be embedded in the halftoning algorithm, or used to predict the printed halftone image at the input to an algorithm being used to assess print quality. In our research, we …
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The structure of promises in quantum speedups
It has long been known that in the usual black-box model, one cannot get super-polynomial quantum speedups without some promise on the inputs. In this thesis, we examine certain types of symmetric promises, and show that they also cannot give rise to super-polynomial quantum speedups. We conclude …
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Autonomous data collection techniques for approximating marine vehicle kinematics
… While the parameters of many physical dynamic models can be obtained using System Identification (SI) techniques, these models require knowledge of the vehicle actuators, which may not be the case in a "backseat driver" architecture using payload autonomy. Even when an identified physical model …
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STATISTICAL LEARNING FOR STANDARD MODEL PHENOMENOLOGY
… both in terms of parametrization and model selection. We discuss different sources of PDF uncertainty. First, we elucidate the nontrivial aspects of averaging over the space of PDF determinations by explicitly calculating the data-driven correlation between different sets of PDFs. …
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Identifying and Predicting Rat Behavior Using Neural Networks
… <p>In this thesis, neural networks are used as a black-box model to map electrophysiological data, representative of an ensemble of neurons in the hippocampus, to a T-maze, wheel running or open exploration behavior. The velocity and spatial coordinates of the identified behavior are then …
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AutoDiff: A Scalable Framework for Automated Model Comparison
… reinforcement learning can cause large language models (LLMs) with identical architectures to exhibit divergent behaviors. However, the mechanisms driving these behavioral shifts remain largely opaque, limiting the reliability and interpretability of adapted models. AutoDiff is a scalable, …
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Modeling, identification, and application of multilayer polypyrrole conducting polymer actuators
… actuators to develop low-order lumped parameter models of actuator electrical, mechanical, and electromechanical behavior. Experimental data were processed using system identification techniques. Both grey box and black box models were identified. The grey box model consisted of a first order …
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Model-Based Testing of Smart Home Systems Using EFSM, CEFSM, and FSMApp
… and FSMApp [10] to generate reusable test-ready models of smart home systems. We present an approach to create reusable test-ready models of smart home systems using EFSMs to model device components (Sensor, Controller and Actuator), EFSMs to model single devices in the SHS and the interaction …
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Hybrid neural networks models for a membrane reactor
… of "hybrid artificial neural networks" (HANN) models that combine both the deterministic and the ANN elements. Several methods have been proposed for combining ANN with first principle relations. In this thesis, a new hybrid scheme, which is similar to that developed by Kasprow for a …
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Explaining Black-Box Classifiers by Implicitly Learning Decision Trees
… of objects that explain the classification of a black-box model f : {±1}^d → {±1} on an instance x ∈ {±1}^d . The first is a certificate: a small set of x’s features that in conjunction essentially determines f(x). The second is a counterfactual: a nearest instance x′ for which f(x′) ≠ f(x). We …
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Generalized Terminal Modeling of Electro-Magnetic Interference
Terminal models have been used for various power electronic applications. In this work a two- and three-terminal black box model is proposed for electro-magnetic interference (EMI) characterization. The modeling procedure starts with a time-variant system at a particular operating condition, which …
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STUDYING PRODUCT REVIEWS USING SENTIMENT ANALYSIS BASED ON INTERPRETABLE MACHINE LEARNING
… analysis, we consider the use of both glass-box (rule-based) and black-box opaque (BERT) models. We find that while the black-box model is more correlated with product ratings, there are interesting counterexamples where the sentiment analysis results by the glass-box model are better aligned …
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Improvements of and Extensions to FSMWeb: Testing Mobile Apps
… these first. We present an approach to generate black-box tests to test fail-safe behavior for web applications. We apply the approach to a large commercial web application. The approach uses a functional (behavioral) model to generate tests. It then determines at which states in the execution of …
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Continuum Mechanics of Duhem’s Approach to Hysteresis
Although the Duhem model of hysteresis was introduced in the late nineteenth century, it has not received particular attention for nearly a century. Only in the late twentieth century did researchers begin to cite and attribute this model to Pierre Duhem, employing it as a “black-box model” in …
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Forecasting linehaul transit times & on time delivery probability using quantile regression forests
… them into quantile regression forest, a black box forecasting model, that will provide estimated scheduled transit times for a given probability of on-time arrival at the destination. With the use of Amazon's Q1 & Q2 2013 linehaul data, an analysis on performance trends based on length of …
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Intelligent algorithms applied to weather radar based flood forecasting system
… a large variety of operational flood forecasting models were supplied from SW Region of the Environment Agency. Data processing, the selection of a suitable model, model calibration and parameters updating have played a more and more important role in real time forecasting and this thesis focuses …
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Modeling and Control of the Paper Machine Drying Section
The topic of this thesis is modeling and control of the last part of the paper machine - the drying section. Paper is dried by letting it pass through a series of steam heated cylinders and the evaporation is thus powered by the latent heat of vaporization of the steam. The moisture in the paper is …
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Faster algorithms for convex and combinatorial optimization
… algorithm for convex problems under the black box model. As a corollary, this implies a polynomially faster algorithm for three fundamental problems in computer science: submodular function minimization, matroid intersection, and semidefinite programming. --Graph Sparsification: We obtain …
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