Browsing by Subject "Deep Learning"
Now showing items 1-3 of 3
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The First Exit-Time Analysis of an Approximate Barndorff-Nielsen and Shephard Model, with Data Science-Based Applications in the Commodity Market
(North Dakota State University, 2021)In this dissertation, an approximate version of the Barndorff-Nielsen and Shephard model, driven by a Brownian motion and a Lévy subordinator, is formulated. The first-exit time of the log-return process for this model is ... -
Sentiment Analysis of COVID-19 Vaccination Impact on Twitter Tweets Using NLP Supervised Learning and RNN Classification Comparison
(North Dakota State University, 2022)Twitter provides a platform for exchanging information and opinions on global concerns like the COVID-19 epidemic. During the COVID-19 pandemic, we used a collection of around 16,180 tweets to derive inferences regarding ... -
A Study on Deep Learning for Prognostics and Health Management Applications: An Evolutionary Convolutional Long Short-Term Memory Deep Neural Network Data-Driven Model for Prognostics of Aircraft Gas Turbine
(North Dakota State University, 2022)The fundamental concept of prognostics and health management (PHM) within the scope of Condition-Based Maintenance (CBM) is to find an approach to evaluate the system health and predict its remaining useful life (RUL). ...