Browsing OU - Theses by Subject "Machine learning"
Now showing items 1-8 of 8
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Assessment of spectral attributes in identifying gas hydrates in seismic data from the Pegasus Basin, offshore New Zealand
(2023-05-13)Gas hydrates are formed in the subsurface along shallow ocean basins or in permafrost settings, and are commonly identified in the seismic data by the bottom-simulating reflector (BSR). Various methods have been employed ... -
Automatic Leak Detection in Carbon Sequestration Projects
(2020-05-15)The international commitments for carbon capture will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful carbon sequestration project lies in the long term storage and ... -
CONNECTIVITIES OF VARIOUS COMPONENTS IN ORGANIC-RICH SHALE
(2019)The physical properties of shale are fundamentally controlled by its microstructure. Connectivity of various components in shale is an important property that governs the transport of mass, energy and momentum. Quantifying ... -
Enhancing Performance and Reducing Emissions in Natural Gas Aspirated Engines through Machine Learning Algorithm
(2023-12-15)In an era where the global energy landscape is increasingly defined by the dual imperatives of efficiency and sustainability, the natural gas sector stands at a crucial juncture. The engines powering this sector, especially ... -
Investigating the potential of synthetic data for enabling AI-based zero-touch network automation
(2021)The essence and importance of rich and relevant data can not be overemphasized in the field of artificial intelligence. From machine learning to deep learning models, the performance of a model is majorly dependent on the ... -
Respiratory Rate Estimation Using WiFi Channel State Information - A Machine Learning Approach
(2020)Respiratory rate (RR) is an important vital sign for diagnosing and treating a number of medical conditions. Current respiration monitoring systems require that a special device is continuously attached to the human body. ... -
SUB-SEISMIC REEF CHARACTERIZATION USING MACHINE LEARNING AND MULTI-ATTRIBUTE ANALYSIS
(2020)Historically, Silurian reef complexes in the Michigan Basin have been largely identified using 2D seismic surveys with very little research focusing on characterizing these reefs (morphology, internal architecture, reservoir ... -
Using Machine Learning to Predict Damaging Straight-line Convective Winds
(2016-08-12)Thunderstorms, including straight-line (non-tornadic) winds, cause an average of over 100 deaths and $10 billion of insured damage per year in the United States. In the past decade machine learning has led to significant ...