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 114 for “"Data-driven models"”.
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Data Driven Models for Language Evolution
… biological sequence analysis, we have designed a data driven orthographic learning system for measuring string similarity and we have successfully applied it to the tasks of cognate identification and phylogenetic inference. Our system has outperformed the best comparable phonetic and orthographic …
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Data-driven models for turbulent separated flows
L'abstract è presente nell'allegato / the abstract is in the attachment
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Hybrid data-driven models of machine translation
… representing two different frameworks within the data-driven paradigm. EBMT has always made use of both phrasal and lexical correspondences to produce high-quality translations. Early SMT models, on the other hand, were based on word-level correpsondences, but with the advent of more sophisticated …
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Data-driven models of water and methane
… of materials modelling, traditional atomistic models seldom achieve high accuracy and speed at the same time. Recent developments using high-dimensional fits to approximate the quantum chemical potential energy surface (PES) have overcome this problem. This thesis presents such models for …
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Advances in data-driven models for transportation
… to changing needs. To this end, we provide four models of transportation planning that are based on data and driven by optimization. A key aspect is the ability to provide certificates of optimality, while being practical in generating high-quality solutions in a short amount of time. We provide …
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Data-driven models for uncertainty and behavior
… has seen an explosion in the availability of data. In this thesis, we propose new techniques to leverage these data to tractably model uncertainty and behavior. Specifically, this thesis consists of three parts: In the first part, we propose a novel schema for utilizing data to design …
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Data-driven models for reliability prognostics of gas turbines
This thesis develops three data-driven models of a commercially operating gas turbine, and applies inference techniques for reliability prognostics. The models focus on capturing feature signals (continuous state) and operating modes (discrete state) that are representative of the remaining useful …
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Data-Driven Models to Enhance Physically-Based Groundwater Model Predictions
… and predictions intervals. The percentage of data coverage by the intervals is improved by as much as 88%, while the width of the intervals is diminished.
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Optimization under moment, robust, and data-driven models of uncertainty
… solutions obtained from other approaches such as data-driven and robust optimization approach. Our approach shows that minimax solutions hedge against worst-case distributions and usually provide low cost variability. We also extend the moment-based framework for multi-stage stochastic …
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Development of Data-driven Models to Predict Vs30 from mHVSR
… velocity in the upper 30 meters (VS30) using data-driven models. We develop a dataset comprising 536 sites with 2,861 three-component ambient noise recordings from global regions, including New Zealand, Taiwan, Italy, Ecuador, Mexico and the United States. The identically processed …
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Use of data-driven models to improve prediction of physically based groundwater models
… model structural error, parameter error and data error. The model uncertainty can be difficult to quantify, and is propagated to the prediction. In this study, complementary data-driven models (DDMs) are used to improve prediction of groundwater flow models. The DDMs, trained with the …
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Deep neural networks as data-driven models for flow and transport in porous media
L'abstract è presente nell'allegato / the abstract is in the attachment
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Data-driven models to evaluate root causes of energy performance gaps in office buildings
… achieving predicted energy goals of the project. Data-driven models, based on the actual building energy consumption data, offer an excellent means to evaluate significant root-causes of energy performance gaps; occupancy, envelope and HVAC operations. On the one hand, this supports the feedback …
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NON-DIMENSIONAL DATA-DRIVEN MODELS OF COMPUTATIONAL FLUID DYNAMICS (CFD) OF MULTI-PHASE FLOW IN ANNULUS
… established. In addition, two non-dimensional data-driven models were developed to describe the cavitation conditions in terms of downstream/upstream pressure ratio and non-dimensional geometric parameters. The first model evaluated the critical downstream/upstream pressure ratio to cause …
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Guiding the development of data-driven models to solve constitutive inverse problems in medical elasticity imaging
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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Using Data-Driven Models to Understand Transition Metal Catalyst Energy Landscapes and Metal-Organic Framework Stability
… opportunity for non-linear machine learning (ML) models that can be used over a larger space of candidate materials. Rather than relying on linear relationships between quantities, ML models can be trained to directly predict catalyst reactivity on the basis of chemical composition and applied to …
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Robust and Data-Driven Uncertainty Quantification Methods as Real-Time Decision Support in Data-Driven Models
The growing complexity and data in modern engineering and physical systems require robust frameworks for real-time decision-making. Data-driven models trained on observational data enable faster predictions but face key challenges—data corruption, bias, limited interpretability, and uncertainty …
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Achieving Security and Reliability of Industrial Control Systems Using Data-Driven Models Informed by Physical Domain Knowledge
… infiltrating either the supervisory control and data acquisition (SCADA) systems or programmable logic controllers (PLCs) and disrupting process activity. To cause these disruptions, attacks inject malicious commands or falsify sensor data to cause the physical process to deviate away from …
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Revamping Manufacturing Systems: Utilization of Data Driven Models, Interpretable Machine Learning, and Data-Product Stakeholder Flow Analysis
In the manufacturing environment, high volume of data can be easily generated. However, to provide valuable insight, the right tools, medium, and communication flow within stakeholders are crucial. This thesis presents a comprehensive exploration of developing data products in the manufacturing …
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