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 39 for “"Time Series Modeling"”.
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Essays on Time Series Modeling
… hypothesis for Brazil. In this chapter we use time series techniques to model the long-run dynamics of the Brazilian inflationary process. Our results reveal that, although there is some inertia in the Brazilian inflation, the degree of inertia is rather small. Another important policy issue …
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Time series modeling of text data
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Essays on forward portfolio theory and financial time series modeling
… the application of stochastic and statistical modeling techniques to the problem of optimal portfolio choice and financial time series analysis. The first essay presents turnpike-type results for the risk tolerance function in an incomplete Ito-diffusion market setting under time-monotone for- …
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High resolution time-series modeling of domestic hot water heating systems
… are developed using Matlab Simulink® with a time-step of one minute. Using minute resolution hot water flow, hourly solar radiation data and ambient temperature, the performance of various configurations are assessed when operating in Victoria, Kamloops, and Williams Lake, B.C. Twelve …
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The Effects of Spatial Aggregation on Spatial Time Series Modeling and Forecasting
Spatio-temporal data analysis involves modeling a variable observed at different locations over time. A key component of space-time modeling is determining the spatial scale of the data. This dissertation addresses the following three questions: 1) How does spatial aggregation impact the properties …
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Automatic ARIMA Time Series Modeling and Forecasting for Adaptive Input /Output Prefetching
… demonstrate 30% improvement in total execution time over the traditional Unix file system on three Linux clusters, equipped with different hardware configurations. More importantly, this performance improvement has small memory requirements and is shown to scale with increasing I/O intensity.
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Time series modeling of spot energy prices for strategic fuel management and gas/electricity arbitrage
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
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Adjusting for Autocorrelated Errors in Neural Networks for Time Series
Time series are everywhere and exist in a wide range of domains. Electrical activities of manufacturing equipment, electrocardiograms, traffic occupancy rates, currency exchange rates, speech signals, and atmospheric measurements can all be seen as examples of time series. Modeling time series …
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Modeling Conditional Distribution of Intraday Returns
Time-series modeling of conditional distributions of intraday returns is of great importance to financial professionals and academic researchers. This work contributes to a methodological and empirical body of knowledge on conditional distributions of intraday asset returns. In Chapter 1, we study …
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Statistical and machine learning models for critical infrastructure resilience
… approach, we explore novel data sources and time series modeling techniques to model disaster impacts on power systems through the case study of Hurricane Sandy as it impacted the state of New York. We find a correlation between Twitter data and load forecast errors, suggesting that Twitter …
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A New State Transition Model for Forecasting-Aided State Estimation for the Grid of the Future
… The proposed state forecasting model is based on time-series modeling of filtered system states and it takes spatial correlation among the states into account. Once the states with high spatial correlation are identified, the time-series models are developed to capture the dependency of voltages …
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I Can See What You Are Feeling, but Can I Feel It? Physiological Linkage while Viewing Communication of Emotion via Touch
… from Kissel (2020) using dynamic linear time series modeling. Results showed that physiological linkage can occur between "live" and recorded participants. Participants demonstrated longer linkage times with the initial dyad they viewed, but linkage with videoed communicators whose …
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Characterization of palmer drought index as a precursor for drought mitigation
… In this dissertation three broad schemes i) time series modeling, ii) Markov chain analysis, and iii) dynamical systems approach are put forward for computing the drought parameters necessary for understanding the scope of the drought. These parameters include drought occurrence …
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Temporal changes in marketing mix effectiveness
… knowledge and familiarity with products over time, and (3) changes in market response associated with changes in consumer incomes. In addition, this research investigates (4) changes in the relative effectiveness of marketing mix variables over time. The hypotheses are tested on time series …
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Predicting blood pressure response to fluid bolus therapy in the ICU using attention-based stacked neural networks for clinical interpretability
… system large-scale database. We investigated time-series modeling with the use of the stacked long short term memory network (LSTM) and the gated recurrent units network (GRU) models by altering the representation of our data and time-aggregated modeling using logistic regression algorithms …
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Multivariate time series clustering using kernel variant multi-way principal component analysis
Clustering multivariate time series data has been a challenging task for researchers since data has multiple dimensions to consider such as auto-correlations and cross-correlations whereas multivariate time series data has been prevailing in diverse areas for decades. However, for a short-period …
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Bayesian Analysis of Latent Threshold Dynamic Models
Time series modeling faces increasingly high-dimensional problems in many scientific areas. Lack of relevant, data-based constraints typically leads to increased uncer-tainty in estimation and degradation of predictive performance. This dissertation addresses these general questions with a new and …
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Airline passenger cancellations : modeling, forecasting and impacts on revenue management
… above their physical capacity. At the same time, airlines need to be cautious not to overbook too aggressively. If a flight is still overbooked at time of departure, not all passengers are able to board and those left behind need to be compensated and re-accommodated. This thesis focuses on …
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Sensing and Predicting Urban Rail Platform Crowding Using Emerging Data Sources
… occupancies 15–60 minutes ahead of time. Our results show significant improvements over a WMATA-internal baseline while providing a robust data preparation and prediction pipeline. Subsequently, we explore integrating platform-level CCTV data to overcome the lack of real-time …
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