Browsing OU - Theses by Subject "Machine Learning"
Now showing items 21-34 of 34
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Promoting Speciation Through Variable Dominance in Genetic Algorithms
(2020-05)Genetic algorithms are a class of search algorithms that have been around since the 1970s. Despite their age, genetic algorithms still see a great deal of use in various applications and so many efforts have gone into ... -
Real-Time Gesture Recognition with Mini Drones
(2018-12-14)Drones are being used worldwide to perform many functions - medical deliveries, video recording, and surveying to name a few. Their growing presence is paralleled by the growing world of Machine Learning (ML). This thesis ... -
Reinforcement Learning for Cognitive Phased Array Radar Surveillance
(2023-05-12)The proliferation of phased array radar (PAR) has significantly increased the flexibility of radar systems, making it possible to use a single radar to perform a variety of operational modes such as surveillance and tracking ... -
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. ... -
RWIS based road condition prediction using machine learning algorithms
(2021-06-26)The need for a forecasting model of road conditions is becoming evermore critical, given the effects of ever-increasing severity in weather. Drastic changes in weather, especially cold fronts, often lead to dangerous roads. ... -
Secure Decentralized Decisions in Consolidated Hospital Systems: Intelligent Agents and Blockchain
(2018)Shared decision making has become a very important solution in order to build a consolidated healthcare system. While there is some research in the healthcare literature discussing the advantages and disadvantages of the ... -
Seismic attribute optimization with unsupervised machine learning techniques for deepwater seismic facies interpretation: users vs machines
(2020-07)Machine learning (ML) has many applications within the geosciences, from predicting seismic facies, to automatic fault detection. A variety of machine learning algorithms are commonly employed, among these principal component ... -
Seismic Reprocessing of a Granite Wash Survey, Buffalow Wallow Field, Anadarko Basin, Texas
(2017-12-16)Although considered one of the more productive oil and gas reservoirs in the United States, the Pennsylvanian-age Granite Wash reservoir remain poorly understood. Amongst a myriad of issues that hinder development of ... -
A simulation and analytical study on the performance of gas-liquid centrifugal downhole separators
(2023-12-15)A common issue in depleted oil and gas wells is the lack of energy to drive the fluids to the surface. Engineers use various artificial lift systems to solve this problem, most commonly by using pumps. Many pump types do ... -
A Simulation Study Comparing the Use of Supervised Machine Learning Variable Selection Methods in the Psychological Sciences
(2022)When specifying a predictive model for classification, variable selection (or subset selection) is one of the most important steps for researchers to consider. Reducing the necessary number of variables in a prediction ... -
A supervised machine learning approach to discriminate reservoir fluid presence and saturation in the Gulf of Mexico using frequency and spectral shape attributes
(2023-05-13)The first chapter in this research aims to define reliable attributes to differentiate subsurface fluids and measure their attenuation to provide insights into reservoir properties. The study investigates the effects ... -
Traffic accident analysis and prediction using the NPMRDS
(2020-12)Traffic accidents are incidents caused by collisions between road vehicles or a vehicle with road infrastructures or pedestrians. Traffic accidents are a common cause for non-recurring traffic bottlenecks that, in turn, ... -
Using Machine Learning to Improve the NSSL's Warn-On-Forecast System's Prediction of Thunderstorm Location
(2023-08-04)Deep learning (DL) models have become immensely popular in recent years, with many models creating accurate and high-skill predictions for a wide range of atmospheric phenomena. Using DL models for predicting convection ... -
Video Outpainting using Conditional Generative Adverarial Networks
(2021)Recent advancements in machine learning and neural networks have pushed the boundaries of what computers can achieve. Generative adversarial networks are a specific type of neural network that have proved wildly successful ...