Search
Now showing items 1-10 of 33
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 ...
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 ...
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. ...
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 ...
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 ...
Development of Deep Learning Methodologies for Modeling Navigational Features in Continuous Spaces
(2021-12)
This thesis proposes generalized methodologies to model navigational features of continuous spaces using deep learning architectural approaches. Navigational features impact how an entity can effectively travel within a ...
Evaluating GAM-Like Neural Network Architectures for Interpretable Machine Learning
(2019-05)
In many machine learning applications, interpretability is of the utmost importance. Artificial intelligence is proliferating, but before you entrust your finances, your well-being, or even your life to a machine, you’d ...
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 ...
Analysis of dynamics of road weather information system data
(2023-12)
Road and Weather Information System consists of a network of roadside Environmental Sensor Stations (EES) collecting meteorological data. Equipped with a variety of sensors, these stations gather data including ambient ...