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 16 of 16 for “"bayesian network model"”.
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A Bayesian Network Model of Political Belief Polarisation
In this thesis I explore a rational model of the emergence of mass disagreement about political issues within societies. The model supposes a recursive process whereby people attribute bias to information sources who promulgate views they disagree with, and then down-weight future information …
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Semantically aware hierarchical Bayesian network model for knowledge discovery in data : an ontology-based framework
… framework that integrates the Hierarchical Bayesian Network (HBN) and domain ontology. The ultimate aim of this thesis is to propose a data mining framework that implicitly caters for the underpinning domain knowledge and eventually leads to a more intelligent and accurate mining process. To …
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Bayesian networks for cardiovascular monitoring
… amount of time. In this thesis, I explore Bayesian Networks as a way to integrate patient data into a probabilistic model. I present a small Bayesian Network model of the cardiovascular system and analyze the network's ability to estimate unknown patient parameters using available patient …
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DETECTING DISTRIBUTED DENIAL OF SERVICE ATTACKS IN IPV6 BY USING ARTIFICIAL INTELLIGENCE TECHNIQUES
… to each and every device connected to a network for identification purposes. NDP messages are broadly categorized into five types and each message type carries out distinct tasks, these messages are: Router Solicitation (RS), Neighbour Solicitation (NS), Router Advertisement (RA), …
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Text structure-aware classification
… unsupervised fashion. We develop a Conditional Bayesian Network model that incorporates relevance as a hidden variable of a target classifier. Relevance and label predictions are performed jointly, optimizing the relevance component for the best result of the target classifier. Our work …
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Designing Bayesian networks for highly expert-involved problem diagnosis domains
… involvement in design. This thesis proposes a model which balances the amount of expert involvement needed and the complexity of design in cases where training data for machine learning is limited. This model aims to use a variety of techniques and methods to translate, and augment, experts' …
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UNCERTAINTY QUANTIFICATION OF LANDSLIDE SUSCEPTIBILITY MAPPING USING BAYESIAN NETWORK
… non-landslide points) for machine learning-based model training, and (3) interpreting the causal relationships among factors influencing landslides and uncertainty propagation in model predictions. To address these knowledge gaps, this work presents results of 1) sensitivity analysis to assess the …
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A Knowledge Enriched Computational Model to Support Lifecycle Activities of Computational Models in Smart Manufacturing
… supporting lifecycle activities of computational models in Smart Manufacturing (SM), a Knowledge Enriched Computational Model (KECM) is proposed in this dissertation to capture and integrate domain knowledge with standardized computational models. The KECM captures domain knowledge into …
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Seepage monitoring and diagnosis of distresses in an earth embankment dam using probability methods
… and observed at the downstream toe over time. A Bayesian network model is developed to evaluate the potential sources and related paths associated with the detected flows downstream. The model is completed by developing an approach to estimate the rate of erosion and predict the potential failure …
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Bayesian causal inference of cell signal transduction from proteomics experiments
… and processes signals from the environment using networks of interacting proteins. In computational systems biology, investigators apply machine learning methods for causal inference to develop causal Bayesian network models of signal transduction from experimental data. Directed edges in the …
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A risk-based maintenance methodology of industrial systems
… this goal. Delay-time analysis is a maintenance modelling technique which can achieve such goals in a manufacturing environment. Delay-time analysis, through the input of certain parameters, is capable of establishing an optimum inspection interval from both a downtime standpoint as well as a …
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Context Aware Pre-Crash System for Vehicular ad hoc Networks Using Dynamic Bayesian Model
… of wireless communications and mobile ad hoc networks has led to improvements in intelligent transportation systems heightening these systems’ safety. Vehicular ad hoc Networks comprise an important technology; included within intelligent transportation systems, they use dedicated short-range …
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Managing Complex Water Resource Systems for Ecological Integrity: Evaluating Tradeoffs and Uncertainty
… My research addresses this limitation using two modeling approaches: stochastic system dynamics modeling and Bayesian network modeling. Specifically, the objectives of my research were 1) evaluate the impacts of environmental flow alternatives on other water users within a complex managed basin …
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Analysis and Prediction of the Commuting Mode Choices in England Using Bayesian Networks
… This research aims to develop a novel Bayesian Network (BN) model that enables rapid investigations of complex influences upon travel mode choices through standard travel, place, and work surveys, which would become a new method that complements the existing models. The theoretical …
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Pronóstico probabilístico de caudales de avenida mediante redes bayesianas aplicadas sobre un modelo hidrológico distribuido
… La presente tesis muestra el desarrollo de un modelo de pronóstico probabilístico de caudales con aplicación al proceso de toma de decisiones en una situación real de avenidas. El modelo de pronóstico se fundamenta en la combinación de un conjunto de herramientas que permiten la simulación del …