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 12 of 12 for “"probabilistic forecasting"”.
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Key Concepts and Methods in Point and Probabilistic Forecasting of Electricity Prices
L'abstract è presente nell'allegato / the abstract is in the attachment
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Advances in statistical post-processing of weather forecasts, probabilistic forecasting, and modelling of extreme events
… weather prediction (NWP) models, which give a probabilistic estimate of future weather. However, these ensembles might have biases and errors in dispersion, thus necessitating the application of statistical corrections -- so-called statistical post-processing. In this thesis, I will make some …
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Graph-based Time-series Forecasting in Deep Learning
Time-series forecasting has long been studied and remains an important research task. In scenarios where multiple time series need to be forecast, approaches that exploit the mutual impact between time series results in more accurate forecasts. This has been demonstrated in various applications, …
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Theater level operations other than war modeling : applications of decision making theory
… assistance mission environment. The model uses probabilistic forecasting models and Bayesian techniques to predict what the state of a region in the theater will be some time in the future. Decision tree structures and the forecasting module are used to solve the decision making problem using …
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Operation under Uncertainty in Electric Grid: A Multiparametric Programming Approach
… and decisions are made by incorporating such probabilistic descriptions. To illustrate the new paradigm, we consider two specific problems. For characterization of system uncertainty, we develop a formal methodology for probabilistic forecasting of real-time operations and locational marginal …
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Model post-processing for the extremes: improving forecasts of locally extreme rainfall
This study investigates the science of forecasting locally extreme precipitation events over the contiguous United States from a fixed-frequency perspective, as opposed to the traditionally applied fixed-quantity forecasting perspective. Frequencies are expressed in return periods, or recurrence …
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Enhanced weather modelling for dynamic line rating
… approaches to dynamic line rating (DLR) forecasting provide single point estimates with no indication of the distribution of possible errors. Furthermore, most research related to DLR forecasting deals only with continuous or steady-state ratings while less attention has been given to …
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Forecasting and trading optimisation in the day-ahead and balancing market
… The research outlines how to approach forecasting the BM, starting with the collection and preprocessing of datasets for both the Irish DAM and BM, accompanied by a detailed time series analysis. Various techniques for forecasting electricity prices are investigated, utilising …
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Probabilistic Models for Human Migration Forecasting and Residency Imputation
I develop probabilistic models to enhance the estimation and forecasting of human migration flows and residency. Using a Bayesian hierarchical approach, I first propose a model for forecasting global bilateral migration flows among the 200 most populous countries, producing well-calibrated …
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Stochastic Dynamically Orthogonal Modeling and Bayesian Learning for Underwater Acoustic Propagation
… and verify differential equations for efficient probabilistic underwater acoustic modeling in uncertain environments; (2) develop theory and implement algorithms for the Bayesian nonlinear inference and learning of the ocean, bathymetry, seabed, and acoustic fields and parameters using sparse …
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Developing a Probabilistic Stock Turnover System Dynamics Model to Forecast Whole-life Energy of Chinese Urban Residential Building Stock
… Gamma and Gumbel distributions. For each, the probabilistic stock turnover model is simulated using Markov Chain Monte Carlo (MCMC) methods. BMA is then applied to combine model-specific predictions of the historical stock evolution based on the respective probabilities of the five survival …