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 167 for “"Model-free"”.
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Model-free learning with imitation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Model-Free Variable Selection through Sufficient Dimension Reduction
… selection to develop new theory and methods for model-free variable selection. After developing the natural connection between sufficient dimension reduction and model-free variable selection we introduce two approaches to select independent variables important to predicting the response variable …
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Toward model-free and reference-free quantitative ultrasound
… target and the feasibility of reference-free quantitative ultrasound using a convolutional neural network. The sensitivity of CNN in a reference-free environment is assessed and experimentally validated. A model-free approach through the use of principal component analysis is proposed as …
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Information-theoretic Algorithms for Model-free Reinforcement Learning
In this work, we propose a model-free reinforcement learning algorithm for infinte-horizon, average-reward decision processes where the transition function has a finite yet unknown dependence on history, and where the induced Markov Decision Process is assumed to be weakly communicating. This …
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Model free real-time optimization for vapor compression systems
… insufficient information for a reliable system model is available. An alternative set of optimization approaches use system measurements. This thesis focuses on one such approach, extremum seeking control, which uses performance index measurements to determine optimal system settings. Forgoing …
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Population pharmacokinetics: model-free approach and nonlinear mixed-effects modelling
… hi the first part of the thesis, a new, model-free approach is developed and tested. It introduces a model-free measure of patient's exposure to drugs, and then investigates the relationships between the exposure level and covariates using various statistical techniques. Classification …
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A Model-Free Approach for Classification of fMRI Brain Images
This dissertation considers the problem of classifying subjects into predefined groups based on functional magnetic resonance imaging (fMRI) data. Classification of subjects into predefined groups, such as patient vs. control, based on their functional MRI data is a potentially useful procedure for …
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Model-free reinforcement learning in non-stationary Markov Decision Processes
… with an initially unknown environment, usually modeled by a Markov Decision Process (MDP). The classical RL literature typically assumes that the state transition functions and the reward functions of the MDP are time-invariant. Such a stationary model, however, cannot capture the dynamic nature …
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Analysis of Model-Free Control of Wind Farms Using Large-Eddy Simulations
… of wake interactions. In this dissertation, model-free control strategies for wind farm power maximization have been evaluated using numerical simulations of the flow through wind farms. A model-free approach does not require a priori assumptions on the physical system, but learns on-line the …
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Model-Free Variable Screening, Sparse Regression Analysis and Other Applications with Optimal Transformations
… selection methods play important roles in modeling high dimensional data. Variable screening is the process of filtering out irrelevant variables, with the aim to reduce the dimensionality from ultrahigh to high while retaining all important variables. Variable selection is the process of …
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Dynamic Modeling and Model-Free Real-Time Optimization for Cold Climate Heat Pump Systems
… Previous work has paid great efforts in model based strategies, anchored on deriving system models with simulation and experimental testing. Such approaches can be prohibitively expensive due to the inherent nonlinear nature of refrigeration systems and unmeasurable equipment degradation. …
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Model-free tracking control of an optical fiber drawing process using deep reinforcement learning
… training, it outperformed other control models such as open-loop control, proportional-integral (PI) control, and quadratic dynamic matrix control (QDMC) in terms of diameter error. It does not require analytical or numerical model of the system dynamics unlike model-based approaches such …
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Interpolated Experience Replay for Improved Sample Efficiency of Model-Free Deep Reinforcement Learning Algorithms
… NMER using learned Gaussian Process Regression models defined over a transition’s neighborhood. These interpolated transitions, predicted via Bayesian linear smoothing, are then used to update the policy and value functions of deep reinforcement learning agents in a likelihood-weighted fashion. …
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Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments
… budgeted time and resources. However, a correct model of the environment is not typically available in advance, requiring the policy to be learned from data. Model-free reinforcement learning (RL) is a promising candidate for agents to learn control policies while engaged in complex tasks, …
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Model Free Human Pose Estimation with Application to the Classification of Abnormal Human Movement and the Detection of Hidden Loads
… the use of an explicit spatial or temporal model. The visual detection of hidden loads through passive visual analysis of gait is presented as a test of the system. The major contributions of this thesis are in two areas. The first is a neural network based scheme that classifies walking …
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Current based condition monitoring of electromechanical systems. Model-free drive system current monitoring: faults detection and diagnosis through statistical features extraction and support vector machines classification.
… minimise their off times. The author proposes a model free sensor-less monitoring system, where the only monitored signal is the input to the induction motor. The thesis considers different methods available in literature for condition monitoring of induction motors and adopts a simple solution …
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Addressing Indirect Functional Connectivity in Neuroscience via Graphical Information Theory: Causality and Coherence
… are more relevant for neural data. Previous model-free methods have limited ability to identify indirect connections because of inadequate scaling with dimensionality. This poor scaling performance reduces the number of nodes, e.g. brain regions, that can be included in conditioning. By …
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Efficient Online Scheduling in Distributed Stream Data Processing Systems
… <p>In this dissertation, we first propose a model-based approach that accurately models the correlation between a scheduling solution and its objective value (i.e. average tuple processing time) for a given scheduling solution according to the topology of the application graph and runtime …
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Design Distributed Control and Learning Algorithms for a Team of UAVs for Optimal Field Coverage
… the problem by two distinct approaches: one is model-based and the other is model-free. In the first part, we proposed a model-based control framework for UAV teaming to monitor and track a dynamic field like wildfire spreading. Wildfire is well-known for their destructive ability to inflict …
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