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.
Results
Showing 1 to 20 of 58 for “"Data-Driven Model"”.
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Theory-constrained Data-driven Model Selection, Specification, and Estimation: Applications in Discrete Choice Models
… applications, for carefully bringing data-driven flexibility to the specification and model selection of discrete choice models; while, at the same time, maintaining usability for analysis. Assumptions brought to bear under the classical theory-based paradigm enjoy varying degrees of …
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Data-driven model-based approaches to condition monitoring and improving power output of wind turbines
… condition estimation method are the proposed. A modelbased CM approach for wind turbines based on the extreme learning machine (ELM) algorithm and analytic hierarchy process (AHP) are used to estimate health condition of the wind turbine. Essentially, the aim of the proposed method is to make the …
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Developing a data-driven model for dynamic reservoir operation using a combined hidden Markov-decision tree and classification tree algorithms
… extends the hidden-Markov-decision tree (HM-DT) model developed by Zhao and Cai (2020) and proposes a data-driven reservoir operation model (DROM). The HM-DT model is first applied to individual reservoirs to derive sets of representative operation modules. Then a module classification model …
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An evaluation of a data-driven approach to regional scale surface runoff modelling
Modelling surface runoff can be beneficial to operations within many fields, such as agriculture planning, flood and drought risk assessment, and water resource management. In this study, we built a data-driven model that can reproduce monthly surface runoff at a 4-km grid network covering 13 …
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Automated Estimation of ISIP and Friction Losses in Hydraulic Fracture Treatment Falloff Data
… loss from hydraulic fracture treatment falloff data. It illustrated friction loss estimations for 270 stages in 16 shale gas wells drilled from the same pad. The resulting estimates reflect a combination of formation and well completion variations. However, the effort required to analyze each …
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Hierarchical Control of Constrained Multi-Agent Legged Locomotion: A Data-Driven Approach
… we consider emulating the Single Rigid Body model through the use of Behavioral Systems Theory, resulting in a data-driven model that adequately describes a quadruped at the reduced-order level. Still, due to the complexity and a considerable number of variables in the problem, the model …
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Modeling and prediction of residential service transformer’s demand considering high penetration of electric vehicles
… by electric vehicles charging. In this thesis, a data-driven model is developed to predict the transformer’s demand when considering large penetration of electric vehicles, which is then used to estimate the transformer’s economic capacity. The proposed model enables more accurate, economical, and …
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Protein Design at Library Scale
… feasibleto create proteins with novel functions, driven by rapid progress in both com- putational modeling and high-throughput experimentation. Modern tools can explore vast sequence-structure spaces and evaluate biomolecular interactions, while experimental assays can now screen billions of …
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Enhancing Grid Reliability With Phasor Measurement Units
… and control in power grids. However,the massive data generated by PMUs raises the questions of how to efficiently utilize the obtained measurements to understand and control the present system. Additionally, to meet the communication requirements between the advanced meters, the connectivity of …
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Artificial Intelligence-Based Prediction of Permeable Pavement Surface Infiltration Rates
… The objective of this research is to develop a data-driven model to predict the infiltration rate of permeable pavements. Four permeable concrete lab specimens were constructed and subjected to clogging cycles while obtaining surface images and infiltration data. An artificial neural network was …
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Mapping multivariate measures of brain response onto stimulus information during emotional face classification
… [63]. However, in the absence of any specific model of the brain response measurements, this and other [60] attempts to parametrically relate stimulus properties to measurements of brain activation are difficult to interpret. In this thesis I consider a blind data–driven model of brain …
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Multi-fidelity Modeling and Reinforcement Learning for Energy Optimal Planning
Modeling the energy consumption of a quadrotor involves complex electrical and physical dynamics, making it difficult to optimize over. We present a sequence-to-sequence multi-fidelity Gaussian process (MFGP) to learn a data-driven model to predict the energy required to fly a given vehicle …
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Data driven low-bandwidth intelligent control of a jet engine combustor
… for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven …
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Data-Driven Optimization of Automated Speed Enforcement Logistics
… during a planning period. This study proposes a data-driven model to classify camera site locations based on the effectiveness of ASE enforcement. Then, a Markov decision process optimization model is presented to find the optimal camera locations at each cycle and the length of the cycles for …
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Data-Driven Approaches for Enhancing Power Grid Reliability
… thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops …
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A GROUNDED THEORY INVESTIGATION OF COUNSELOR EDUCATORS’ SOCIALLY JUST AND CULTURALLY RESPONSIVE COUNSELING LEADERSHIP
… associations and higher education. Participant data were collected over two rounds of semi-structured interviews, member checks, and peer debriefing. The researcher collected and analyzed data using the Straussian tradition of grounded theory combined with the theory of intersectionality to …
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Monotonicity aspects of linguistic fuzzy models
Their interpretable model structure sets linguistic fuzzy m models apart from other modelling techniques and is considered their greatest asset. Therefore, in the identification process of a linguistic fuzzy model, the interpretability of the model should be safeguarded or at least be balanced …
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A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
<p>Creating a data-driven model that is trained on a large dataset of unstructured dialogs is a crucial step in developing a Retrieval-based Chatbot systems. This thesis presents a Long Short Term Memory (LSTM) based Recurrent Neural Network architecture that learns unstructured multi-turn dialogs …
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Study of reduced order models for vortex-induced vibration and comparison with CFD results
… trying to control vibrations; a reduced order model may be an effective way to study the system dynamics. Developing a data driven model from simulation and/or experimental results can be difficult, but there are existing phenomenological models that attempt to describe VIV, several of which …
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