Browsing The University of Oklahoma by Subject "machine learning"
Now showing items 1-20 of 28
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Application of seismic attributes and unsupervised machine learning methods for identification of hidden faults in basement and carbonate rocks
(2023-12-15)Seismic fault interpretation is a critical task for any type of energy industry and correct fault mapping can be crucial for the success of a project. Common geometric seismic attributes such as coherence and curvature are ... -
APPLICATIONS OF MACHINE LEARNING METHODS IN THE GENERATION OF SUBSURFACE MEASUREMENTS
(2018-05-11)Machine learning methods have been used in the Oil and Gas industry for about thirty years. Applications range from interpretations of geophysical, well and seismic responses, identification of minerals, analysis of rock ... -
Applied High-Order Singular Value Decomposition for Weight Compression and Expansion in Deep Neural Networks
(2019-08)Complex deep learning objectives such as object detection and saliency, semantic segmentation, sequence-to-sequence translation, and others have given rise to training processes requiring increasing amounts of time and ... -
Carbon-Based Pollutant Analysis and Remote Sensor Validation Using Column-Observing Fourier Transform Infrared (FTIR) Spectrometers During the TRACER Campaign
(2023-08-04)Greenhouse gases methane (CH4), and carbon dioxide (CO2), along with carbon monoxide (CO), while produced by both anthropogenic and natural sources, all contribute to atmospheric warming. Additionally, CO poses health risks ... -
Correcting, Improving, and Verifying Automated Guidance in a New Warning Paradigm
(2018-05-11)The prototype Probabilistic Hazards Information (PHI) system allows forecasters to experimentally issue dynamically evolving severe weather warning and advisory products in a testbed environment, providing hypothetical end ... -
A Data-Driven Approach For Monitoring And Predictive Diagnosis Of Sucker Rod Pump System
(2022)Given its long operational history, a sucker-rod pump (SRP) has been widely utilized as a lifting solution to bring reservoir fluids to the surface with low cost and high efficiency. However, debugging the rod pump issues ... -
Energy Efficient Machine Learning-Based Classification of ECG Heartbeat Types
(2018-12-05)To meet the accuracy, latency and energy efficiency requirements during real-time collection and analysis of health data, a distributed edge computing environment is the answer, combined with 5G speeds and modern computing ... -
Examining Seismic Amplitude Responses of Gaseous Media Using Unsupervised Machine Learning
(2020-12-18)The presence of gas in the rock’s or sediment’s pore space significantly affects its seismic amplitude response and modifies its subsurface signature. Gas hydrates in the subsurface are often difficult to image with ... -
An Experimental, Modeling and Machine Learning Based Investigation of Stick-Slip Vibrations
(2022-08-04)Drilling technologies have improved considerably since the first well drilled by Colonel E.L Drake in 1859. Drilling technologies enable us to safely drill complex well profiles with advanced downhole tools and sensors to ... -
Exploring Drug-Use Progression Through Stability Enhanced Clustering
(2022-05)Background and aims: Drug use initiation sequences have been the subject of much research, and theories such as the Gateway Hypothesis have been created to explain patterns of progression from common to dangerous drugs. ... -
General supervised learning framework for open world classification
(2020-12-18)In machine learning, the most common scenario for classification modeling is when the training set contains all possible classes and the algorithm learns to identify these classes. The problem setting in which the training ... -
Hydrologic peak flow modelling using machine learning
(2020-12-18)The effect of rainfall spatial variability on catchment responses during floods remains poorly understood. The overall objective of this work is to develop a robust understanding of how rainfall spatial variability influences ... -
Intelligent Condition Monitoring and Prognostic Methods with Applications to Dynamic Seals in the Oil & Gas Industry
(2019)The capital-intensive oil & gas industry invests billions of dollars in equipment annually and it is important to keep the equipment in top operating condition to help maintain efficient process operations and improve the ... -
Kidney OCT 3D images classification using machine learning
(2023-12-15)The goal of this research is to make a classification program for 3D images by using a CNN model. The images to classify are kidney images that have 3 different classes: Pelvis, Medulla and Cortex. To do so, a data ... -
Machine Learning Co-Production in Operational Meteorology
(2022-08)Machine learning, deep learning, and other artificial intelligence (AI) methods are becoming popular tools within the meteorological research community. However, despite the breadth of promising AI research and its ... -
Machine learning enabled query re-optimization algorithms for cloud database systems
(2021-12)In cloud database systems, hardware configurations, data usage, and workload allocations are continuously changing. These changes make it difficult for the query optimizer to obtain an optimal query execution plan (QEP) ... -
Machine Learning Predictions of Flash Floods
(2016-08-12)This dissertation contains a literature review and three studies concerned with the development, assessment, and use of machine learning (ML) algorithms to explore automatically generated predictions of flash floods. The ... -
Modeling Relationships Between Brain/Muscle Activity and Locomotive Behavior
(2022-12)The dynamics of locomotion involve a fine-tuned, continuous feedback loop between processes in the brain, functioning of the muscles, and interactions with the environment. Neurological or motor disability can often disrupt ... -
Nurturing as Safe Exploration Promotes the Evolution of Generalized Supervised Learning
(2017-08-01)The ability to learn is often a desirable property of intelligent systems which can make them more adaptive. However, it is difficult to develop sophisticated learning algorithms that are effective. One approach to the ... -
Question-Answering for Segment Retrieval on Podcast Transcripts
(2022-08)Podcasting has rapidly ascended as one of the primary forms of spoken-word media in the 21st century. The Spotify Podcast Dataset has compiled transcripts of over 100,000 podcast episodes, making it one of the largest ...