Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Graduate Theses and Dissertations
Wildfires have devastating ecological, environmental, economical, and public health impacts through the deterioration of water and air quality, CO2 emissions, property damage, and lung illnesses. The early detection and prevention of wildfires allow for the minimization of these risks. The use of Artificial Intelligence (AI) in wildfire detection and prediction has been highly researched as a tool to assist firefighters in stopping wildfires in its early stages. The three common wildfire prediction categories include image and video detection, behavior prediction, and susceptibility prediction. Data such as climate, weather, vegetation, satellite images, and historical wildfire data is most commonly used. Many …
Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders
Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders
Graduate Theses and Dissertations
The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …