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 18 of 18 for “"Temporal modelling"”.
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Bayesian spatio-temporal modelling, mapping and prediction of disease risk
Η παρούσα διπλωματική εργασία πραγματεύεται τη Bayesian χωροχρονική μοντελοποίηση και χαρτογράφηση του κινδύνου εμφάνισης νόσων, με στόχο την εκτίμηση και πρόβλεψη του σχετικού κινδύνου στον χώρο και στον χρόνο. Η ανάλυση βασίζεται σε ιεραρχικά Bayesian μοντέλα για δεδομένα μετρήσεων τύπου Poisson, …
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Advances in Software and Spatio-Temporal Modelling with Gaussian Processes
… for a class of GPs commonly utilised in spatio-temporal problems. This is a setting in which GPs excel, for example enabling the incorporation of important inductive biases, and observations made at arbitrary points in time and space. However, the computation required to perform exact inference …
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Bayesian spatio-temporal modelling for forecasting ground level ozone concentration levels
… can produce accurate spatial predictions and temporal forecasts.<br/><br/>This thesis focuses on developing spatio-temporal models for interpolating and forecasting ground level ozone concentration levels over a vast study region in the eastern United States. These models incorporate output …
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Spatio-temporal modelling of informal settlement growth using a hybrid GIS and CA-Markov model
… Markov model, to simulate the future spatio-temporal growth of informal settlements in the City of Cape Town, Western Cape, South Africa from 2011 to 2051. To simulate growth, a raster-based model was operationalized using a Computer Simulation Package called TerrSet. The model inputs were …
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Multiscale Spatial and Temporal Modelling of Fine Particulate Matter (PM2.5) from Wildfire Smoke Using Remote Sensing and Statistical Methods
… PM2.5 concentration over space and time. Spatiotemporal models were built to perform a comprehensive analysis of wildfire PM2.5 concentrations, for each recent year over the study region: Land Use Regression (LUR), Linear Mixed Effect (LME), and Artificial Neural Network (ANN). Predictor …
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Spatio-temporal modelling of breast cancer incidence between 2000 and 2021 at sub-national levels in Iran: Bayesian disease mapping
… Iran from 2000 to 2010 using a Bayesian spatio-temporal model. Then, I’ve propagated uncertainty from the spatio-temporal model into the prediction model for the years from 2011 to 2021. The national relative risk of breast cancer incidence in Iran increased from 0.21 (95% credible interval …
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Modeling Urban Venue Dynamics through Spatio-Temporal Metrics and Complex Networks
… city. Through this analysis we demonstrate how temporally similar areas can be successfully used as inputs to predict the visitation patterns of new venues. Next, we forecast the likelihood of business failure through a supervised learning model. We analyze the value of varying features in …
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Speech enhancement using multisensory cooperative computing
… to speech representations with enhanced temporal modelling. Nonlinear transfer functions and a multi-objective loss incorporating mutual information strengthen cross-modal attention. The resulting system improves generalisation, reduces mask complexity, and supports real-time enhancement …
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Integrating contour-coupling with spatio-temporal models in multi-dimensional cardiac image segmentation
… training data, due to the difficulty of modelling 3D or 3D+time structures, that exhibit complex spatial and temporal deformation. This thesis investigates an alternate modelling strategy that is adaptable to changes in structure, and scalable with respect to dimensionality. The major …
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INVASION DYNAMICS OF FRESHWATER CRAYFISH IN A MAN-DOMINATED LAND: SPATIO-TEMPORAL, ECOLOGICAL AND HUMAN DIMENSIONS
… Lombardy (Northern Italy) by integrating spatio-temporal modelling, impact assessment on native fauna, and socio-managerial perspectives. As the latest comprehensive assessment in the region was carried out in 1994–2006 by Fea et al., Chapter 2 aimed first to update invasive crayfish …
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Four essays on statistical modelling of environmental data
… series, and regression analytical approaches for modelling spatio-temporal processes, using air quality data in the applications. The work is structured into four essays the abstracts of which are given in the following. The first essay is titled 'Spatial detrending revisited: Modelling local …
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Computational Bayesian inference using low discrepancy sequences
… effort needed. Lastly, we build a unique spatio-temporal model of residential crime in Hamilton, using INLA’s stochastic partial differential equation approach to a Log-Gaussian Cox Process, and use an LDS to approximate the latent parameters of the model. Our results show that for a fixed number …
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Climate change impacts on landslide susceptibility in the Alpine region using a machine learning approach
L'abstract è presente nell'allegato / the abstract is in the attachment
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Potential for using climate forecasts in spatio-temporal prediction of dengue fever incidence in Malaysia submitted
… The study proposes a potential framework of modelling spatio-temporal variation in dengue risk on a national scale in Malaysia using both climate and non-climate information. Early chapters set the scene by discussing Malaysia and Climate in Malaysia and reviewing previous work on dengue …
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Data-Driven Approaches in Water Pipe Condition Assessment and Failure Prediction
… techniques, numerical methods, and physical modelling to improve failure prediction and support proactive asset management. A key contribution of this work is the development of methods to address the common issue of class imbalance in pipe failure datasets. A semi-supervised clustering …