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 26 for “"average models"”.
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System Simulation Output Analysis by Autoregressive-Integrated Moving Average Models
Made available in DSpace on 2015-05-12T22:38:11Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 7309930.PDF: 5142666 bytes, checksum: 5ae56d3bb78e2c7de46581dcc2c2857c (MD5) Previous issue date: 1972
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New Multi-Phase Diode Rectifier Average Models for AC and DC Power System Studies
… the system smaller, lighter and more reliable. Average models provide a good solution to system simulation and can also serve as the basis to derive the small signal model for system-level study using linear control theory. A new average modeling approach for three-phase and nine-phase diode …
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Observer based fault detection filters for three-phase inverters and statcoms
… for fault detection and isolation. While average models have been proposed for fault detection, these average models disregard dynamics at switching frequency, which are sometimes crucial in determining the exact health of power electronic circuit components. This thesis develops and …
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Modeling and control of three-phase PWM converters
Switching and average models are developed for major three-phase PWM converters. The models are correct for the case when the voltage sources or capacitors with nonzero parasitic resistances are placed across the converter dc port or ac terminals. The effects of the parasitic resistances are …
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NONUNIFORMLY AND RANDOMLY SAMPLED SYSTEMS
… Parameter estimation of autoregressive moving average models using partial observations and an algorithm to fill in the missing data are proved and demonstrated by simulation programs. Interpolation of missing data using bandlimiting assumptions and discrete Fourier transform techniques is …
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Modeling, Analysis, and Design of Distributed Power Electronics System Based on Building Block Concept
… block concept, the discrete and large signal average models are developed for simulation, design, and analysis of large-scale PEBB-based systems. New average models are developed for half-bridge PEBB module and Space Vector Modulation (SVM). These models keep the exact information of the …
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Calibrating high frequency trading data to agent based models using approximate Bayesian computation
… method of calibration for the use of agent based models in market micro-structure. To date, there are no successful calibrations of agent based models to high frequency trading data. Here we test whether a more sophisticated calibration technique, SMC ABC, will achieve this feat on one of the …
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Patterns and associations with immunologic response in patients accessing ART in Khayalitsha
… simple linear regression and population average models were used to make the analysis and report the findings.
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Developing Pattern and Anomaly Detection Methods in Influence Campaigns
… August 2021. Statistical methods included moving average models and Singular Spectrum Analysis (SSA). Machine learning techniques included the use of an autoencoder and an LSTM neural network. These methods provide different ways to visualize and characterize the data. Together, the approaches …
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Comparative analysis of high input voltage and high voltage conversion ratio step-down converters equipped with silicon carbide and ultrafast silicon diodes
… both theoretically, with the use of steady-state average models, and experimentally the substantial efficiency benefits of the use of reverse-recovery free silicon carbide diodes in the conventional buck converter and the small but significant improvement in the efficiency of the isolated …
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Modeling of Power Electronics Distribution Systems with Low-frequency, Large-signal (LFLS) Models
… a modeling methodology that uses new types of models called low-frequency, large-signal models in a circuit simulator (Saber) to model a complex hybrid ac/dc power electronics system. The new achievement in this work is being able to model the different components as circuit-based models and to …
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Current-Mode Control: Modeling and its Digital Application
… peak current-mode control. However, few models are available for variable-frequency constant on-time control and V2 current-mode control. It's hard to directly extend the model of peak current-mode control to those controls. Furthermore, there is no simple way of modeling the effects of …
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The analysis of some bivariate astronomical time series
… and appropriate univariate autoregressive moving average models given. The results of extensive transfer function fitting using respectively the λ1337 and λ1350 continuum variations as input series, are presented. There is little evidence for a dead time in the response of the emission line …
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Forecasting demand for district heating using different forecasting methods
… system. This thesis compares five different models for such forecasts. First, the Auto-Regressive Integrated Moving Average model, or ARIMA, predicted the general average usage based on previous data and was used as a benchmark for other models. Another regression model was created, LOWESS or …
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Stochastic delay difference and differential equations: applications to financial markets
… chapter deals with the behaviour of moving average models of price formation. We show that the asset returns are positively and exponentially correlated, while the presence of feedback traders causes either excess volatility or a market bubble or crash. These results are robust to the …
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Portmanteau Tests For Univariate And Multivariate Time Series Models
… was developed for vector autoregressive moving average models, which is based on exponential weights of the residual covariance matrix. For this new multivariate portmanteau test the asymptotic distribution was derived. This new test was compared with previous tests using Monte Carlo …
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A semantics based computational model for word learning
… proposed semantics-based model outperforms (on average) models that do not use word semantics (semantics-free models). A subject level analysis of results reveals that different models perform well for different children, thus motivating the need to combine predictions. To this end, I present …
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Transformed-linear models for time series extremes
… nonnegative regularly-varying time series models that are constructed similarly to classical non-extreme ARMA models. Rather than fully characterizing tail dependence of the time series, we define the concept of weak tail stationarity which allows us to describe a regularly-varying time …
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Using Mobile Monitoring and Vehicle Emissions to Develop and Validate Machine Learning Empirical Models of Particulate Air Pollution
… variety of locations to develop hourly empirical models of particulate air pollution. This study uses secondary data describing BC and PN pollutant levels, which are obtained from roads that bikers share in the more rural location of Blacksburg (VA). Machine learning (ML) algorithms are then built …
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Application of remotely sensed environmental variables for predicting malaria cases in Nkomazi municipality South Africa
… Seasonal autoregressive integrated moving average models (SARIMA) was developed. The level of prediction, either under-prediction where predicted is less than observed or over-prediction where predicted is greater than observed, are within 10% of the notified malaria cases for all …
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