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 543 for “"Prediction Models"”.
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Development of Pavement Prediction Models
… investigation of the development of pavement prediction models. It addresses a crucial need to develop improved prediction models for various pavement applications such as design, evaluation, rehabilitation, and network management systems.
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Large scale prediction models and algorithms
… properties of a given problem to come up with models applicable in practice, while keeping most of the value of a large data set. Our first application provides a provably near-optimal pricing strategy under large-scale competition, and our second focuses on capturing the interactions between …
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Reactive Prediction Models for Cloud Resource Estimation
… service, etc. More precisely, four mathematical models are first proposed to deal with different situations. Then, a reactive model combining these four models is introduced. Simulations based on CloudSim are designed and implemented. The simulation results for all models meet the expectations …
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Fair and Interpretable Mathematical Methods for Prediction Models
… interpretability, and accuracy of different models from a Bayesian perspective, taking advantage of this framework to quantify uncertainty in predictions as well as in the different fairness metrics implemented, so that trade-offs between objectives can be assessed in a robust way. The main …
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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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An investigation into unifying early warning prediction models
… on worldwide economies. Financial distress models are in existence and have been tested with varying results of success. However, there are varying definitions of financial distress which have contributed to the in-cohesiveness of financial distress literature where users have a limited …
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A re-examination of two major bankruptcy prediction models
This thesis examines two major bankruptcy prediction models existing in the literature: Altman's Z-score model and Ohlson's probabilistic model. The objective is to test whether the model parameters have changed from what they were when Altman and Ohlson originally estimated their models. Two …
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Optimizing Perceptual Quality Prediction Models for Multimedia Processing Systems
L'abstract è presente nell'allegato / the abstract is in the attachment
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Development of flood prediction models using machine learning techniques
… learning. To leverage these algorithms, new models must be developed to efficiently capture the relationships among the variables that influence these events in a given region. These models can be used by emergency management personnel to develop more robust flood management plans for …
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Approaches to developing clinically useful Bayesian risk prediction models
Prediction of the presence of disease (diagnosis) or an event in the future course of disease (prognosis) becomes increasingly important in the current era of personalised medicine. Both tasks (diagnosis and prognosis) are supported using (risk) prediction models. Such models usually combine …
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Study of Human Factors Variables in Battle Outcome Prediction Models
<p>Over time there have been many improvements in models that are used to predict the outcome of battles. Currently there is much supposition and speculation surrounding the use of human performance related factors as additional inputs to battle simulation models to improve their accuracy. However …
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Risk prediction models for hip fracture: parametric versus Cox regression
… due to high morbidity, mortality and cost. Risk prediction models can aid clinical decision-making by identifying individuals at risk. Objective: To build risk prediction model for incident hip fracture using Weibull regression and compare this with Cox regression model. Method: The Study of …
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Network-Level Safety Prediction Models for Long-range Transportation Planning
… by incorporating a network-based collision prediction model (NCPM) as a fifth step in the traditional four-step RTM modelling structure, allowing the model to predict the number of collisions on major and local roads at the planning stage. In addition to traditional estimates of traffic …
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Cardiovascular disease risk prediction models: does one-score-fit-all?
… the need for precise and equitable risk prediction tools. The changing landscape of CVD, partly due to the COVID-19 pandemic disrupting patterns of CVD incidence and care delivery, and partly due to the rising prevalence of obesity, unhealthy lifestyle factors and chronic conditions, …
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Development of prediction models for cardiovascular disease risk in China
… rated across China could be advantageous. Risk prediction models are an integral part of CVD prevention guidelines and can be used to help guide intervention. However, there is no model generalizable to the various incidence, risk-factor levels, and composition of CVD (proportion of CHD and …
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Cluster techniques and prediction models for a digital media learning environment
The present work applies well-known data mining techniques in a digital learning media environment in order to identify groups of students based on their pro le. We generate identi able clusters where some interesting patterns and rules are observed. We generate a neural network predictive model …
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Methods for imbalanced data in sports analytics: improving injury prediction models
… remain rare events, and many existing injury prediction models struggle to identify injury cases accurately. This research evaluates both real-world sports injury datasets and artificial datasets to develop and illustrate a practical framework for modeling and evaluating prediction under …
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Development and validation of volume-to-capacity based accident prediction models
This study is focused on the relationship between accidents and the traffic/geometric capacity of highways. By using regression analyses, this research is conducted to quantify the effects of traffic-to-capacity associations upon the number of accidents on different highway types. A concept of …
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Dynamic risk adjustment of prediction models using statistical process control methods
Introduction. Models that represent mathematical relationships between clinical outcomes and their predictors are useful to the decision making process in patient care. Many models, such as the score of neonatal physiology (SNAP II) that predicts in-hospital mortality, have been well validated on …
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