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 17 of 17 for “"Event prediction"”.
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Clinical event prediction and understanding with deep neural networks
Real-time prediction of clinical interventions remains a challenge within intensive care units (ICUs). This task is complicated by data sources that are noisy, sparse, heterogeneous and outcomes that are imbalanced. In this thesis, we integrate data from all available ICU sources (vitals, labs, …
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Event prediction for modeling mental simulation in naturalistic decision making
… performs in the human range with respect to prediction and decisions. This research shows that entities in a combat simulation environment having the capability of looking ahead into the near future based on statistical data perform more realistically than those that just use the information …
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Representation learning in multi-dimensional clinical timeseries for risk and event prediction
… new representation that are markers of important events. We argue that these latent representations are useful markers when they 1) create better prediction results on outcomes of interest, and 2) do not duplicate features that are currently known bio-markers. We present four case studies of …
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Time-to-Event Prediction Using Deep Learning Models: Application to GPU Failure Data
… for effectively maintaining GPU systems and preventing issues related to GPU failures, such as safety concerns and interruptions in simulations. Most studies concentrate on predicting the remaining lifespan of GPUs, whereas our objective is to predict both lifespan and failure status. …
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Statistical Methods for Multivariate Functional Data Clustering, Recurrent Event Prediction, and Accelerated Degradation Data Analysis
… data. In order to cluster the customized events extracted from multivariate functional data, we apply the functional principal component analysis (FPCA), and use a model based clustering method on a transformed matrix. A penalty term is imposed on the likelihood so that variable selection …
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Improving Clinical Prediction Models with Statistical Representation Learning
… machine learning approaches for healthcare risk prediction applications in the presence of challenging scenarios, such as rare events, noisy observations, data imbalance, missingness and censoring. Such scenarios manifest frequently in practice, and they compromise the validity of standard …
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PhysioMiner : a scalable cloud based framework for physiological waveform mining
… aggregated for windows corresponding to patient events. These aggregated features were fed into DELPHI, a multi algorithm multi parameter cloud based system to build a predictive model. An area under the curve of 0.693 was achieved for an acute hypotensive event prediction from the ECG waveform …
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Limits to extreme event forecasting in chaotic systems
Predicting extreme events in chaotic systems, characterized by rare but intensely fluctuating properties, is of great importance due to their impact on the performance and reliability of a wide range of systems. Some examples include weather forecasting, traffic management, power grid operations, …
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
… Dataset for the 3-days earlier and 1-day earlier event prediction. From the experiments, the improved personalised data modelling using PIfwkNN classifier has shown a significant increase in terms of overall classification accuracy as compared to the conventional MLP, fkNN, and NeuCube with wkNN …
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Applications of Continuous Wavelet Transform in Hydraulic Fracturing and Reservoir Management
… closure identification, dynamic fracture event detection, microseismic event prediction, water hammer modeling, and inter-well connectivity for optimizing waterflooding operations. In fracture closure analysis, the study reviews established methods like the Nolte, tangent, and compliance …
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Labeling and modeling large databases of videos
… to expect. Conversely, when faced with unusual events such as car accidents, humans are very well tuned to identify them regardless of having observed the scene a priori. This is, in part, due to prior observations that we have for scenes with similar configurations to the current one. This …
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Methods of Handling Missing Data in One Shot Response Based Power System Control
… where the authors have described about transient event prediction and response based one shot control using decision trees trained and tested in a 176 bus model of WECC power system network. This thesis contains results from rigorous simulations performed to measure robustness of the existing one …
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Physiological time series retrieval and prediction with locality-sensitive hashing
… similar waveform retrieval to enable critical event prediction in the ICU setting. In order to achieve this goal, we propose to apply locality-sensitive hashing (LSH), which supports a very fast approximate nearest neighbor search in high dimensions. We empirically demonstrate that LSH based …
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Methodological Development with Machine Learning and Bayesian Approaches in Cancer and Nutrition Research
… Data analysis serves two primary purposes: prediction and inference. Inference extracts information to understand associations between predictors (or features) and responses, while prediction consists of forecasting future values based on the current values of predictors and responses. This …
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Learning from multi-modal spatiotemporal data: machine learning approaches to advance resilience in smart grids
… Using spatiotemporal data, a solar generation prediction model was proposed. The solution combined spatial and temporal data, then utilized machine learning embeddings to build datasets to train downstream models. This resulted in accurate prediction of solar generation across several settings. …
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Modelo predictivo de interrupciones del servicio de energía eléctrica domiciliaria de Bogotá usando análisis de datos
La distribución de Energía Eléctrica en la ciudad de Bogotá es fundamental para el crecimiento de la economía local, los usuarios perciben la calidad como la mínima posibilidad de interrupciones y su duración, así como recibir unos parámetros eléctricos aceptables. Para garantizar esta …