Browsing OU - Dissertations by Subject "Machine Learning"
Now showing items 1-20 of 25
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Application of Artificial Neural Networks, Gradient Boosted Decision Trees, and Multilevel Logistic Models in a Supervised Learning Environment to Investigate Differences in Classification Performance when Predicting College Enrollment
(2018-05)The use of data mining algorithms for applied practice is becoming commonplace in many industries. The application of these models to the domain of educational data and practice could provide significant gains in understanding ... -
Application of deep learning to optimize computer-aided-detection and diagnosis of medical images
(2023-12-15)The field of medical imaging informatics has experienced significant advancements with the integration of artificial intelligence (AI), especially in tasks like detecting abnormalities in retinal fundus images. This ... -
Application of Machine Learning to Multiple Radar Missions and Operations
(2022-08-04)This dissertation investigated the application of Machine Learning (ML) in multiple radar missions. With the increasing computational power and data availability, machine learning is becoming a convenient tool in developing ... -
The Context-Aware Learning Model
(2017-12)The ultimate goal of this research is to build a novel, generalized, arbitrary-depth, neural controller that performs reward- and experience-based neuromodulatory learning, which is online, bootstrapping, interactive, ... -
Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction
(2016-08-12)Meteorologists have access to more model guidance and observations than ever before, but this additional information does not necessarily lead to better forecasts. New tools are needed to reduce the cognitive load on ... -
Developing Novel Computer Aided Diagnosis Schemes for Improved Classification of Mammography Detected Masses
(2023-12-15)Mammography imaging is a population-based breast cancer screening tool that has greatly aided in the decrease in breast cancer mortality over time. Although mammography is the most frequently employed breast imaging modality, ... -
Expert-Guided Machine Learning for Meteorological Predictions Across Spatio-Temporal Scales
(2024-08-01)This dissertation emphasizes the contribution of expert knowledge in the development and assessment of machine learning (ML) models within the Earth sciences, specifically Meteorology. Despite the common focus on achieving ... -
FIRST PRINCIPLES MACHINE LEARNING IN RADAR: AUGMENTING SIGNAL PROCESSING TECHNIQUES WITH MACHINE LEARNING FOR DETECTION, TRACKING, AND NAVIGATION
(2024-08-01)Machine learning (ML) provides a set of tools for learning approximate system models from data. It has the potential to improve classic radar signal processing (RSP) algorithms by allowing them to maintain performance when ... -
FRAC HIT ANALYSIS IN SHALES: WOODFORD, MERAMEC AND WOLFCAMP FORMATIONS
(2020-07)Frac hit was initially coined to refer to the phenomenon when an infill well fracture interacts with the adjacent well during the hydraulic fracturing process. But, over the years, its use has been extended to any type of ... -
Interpretable deep neural networks for more accurate predictive genomics and genome-wide association studies
(2023-05)Genome-wide association studies (GWAS) and predictive genomics have become increasingly important in genetics research over the past decade. GWAS involves the analysis of the entire genome of a large group of individuals ... -
Machine Learning Algorithms and Applications in Investment Analysis
(2016-12-16)We can simplify investment analysis as filtering out speculative stocks, bonds, derivatives and other financial products. This area is very challenging yet extremely critical since individual investors’, large institutions’ ... -
Machine learning for classifying biological radar echoes with S-band polarimetric radar
(2023-12-15)The S-band WSR-88D weather radar is sensitive enough to observe biological scatterers like birds and insects. However, their non-spherical shapes and frequent collocation in the radar resolution volume create challenges ... -
Machine Learning for Impact-Based Flash Flood Warnings: Hazard Report Operationalization for Impact Predictions
(2023-12-15)Floods account for approximately one third of all global geophysical hazards, and flash floods allow for extremely short lead times for warnings to be emitted. Flash flood warnings are weather-related alerts which serve ... -
Machine learning for the subsurface characterization at core, well, and reservoir scales
(2020-05-08)The development of machine learning techniques and the digitization of the subsurface geophysical/petrophysical measurements provides a new opportunity for the industries focusing on exploration and extraction of subsurface ... -
NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS
(2015-08-14)An agent may interact with its environment and learn complex tasks based on evaluative feedback through a process known as reinforcement learning. Reinforcement learning requires exploration of unfamiliar situations, ... -
Protecting infrastructure networks from disinformation
(2023-05-12)Massive amount of information shared on online platforms makes the verification of contents time-consuming. Concern arises when the misleading or false information, called "disinformation", is exposed to many online ... -
RESERVOIR CHARACTERIZATION AND MODELING OF A CRETACEOUS TRIPLE POROSITY CARBONATE RESERVOIR CONTRIBUTION OF PORE TYPES TO HYDROCARBON PORE VOLUME AND PRODUCTION, CAMPECHE SOUND, GULF OF MEXICO
(2019-05-10)Campeche Sound, located southeast of the continental shelf in the Gulf of Mexico. represents about 80% of the national hydrocarbons production of Mexico, and comprises several giant oilfields, including Cantarell and ... -
Scaling up Labeling, Mining, and Inferencing on Event Extraction
(2022-05)Numerous important events happen every day and are reported in different media sources with varying narrative styles across different knowledge domains and languages. Detecting the real-world events that have been reported ... -
Search for third generation vector-like leptons with the ATLAS detector
(2022-03-09)The Standard Model of particle physics provides a concise description of the building blocks of our universe in terms of fundamental particles and their interactions. It is an extremely successful theory, providing a ... -
SEISMIC EXPRESSION OF IGNEOUS BODIES IN SEDIMENTARY BASINS AND THEIR IMPACT ON HYDROCARBON EXPLORATION: EXAMPLES FROM A COMPRESSIVE TECTONIC SETTING, TARANAKI BASIN, NEW ZEALAND
(2018-05-11)The impact of Neogene volcanism on hydrocarbon exploration in the Taranaki Basin, New Zealand remains under-explored. To better understand these effects, I performed detailed seismic interpretation coupled with examination ...