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Development of a Safety Performance Decision-Making Tool for Flight Training Organization
PI Marisa Aguiar
CO-I Carolina Anderson
Title 14 of the Code of Federal Regulations (CFR) Part 141 flight training organizations are actively pursuing ways to increase operational safety by introducing advanced risk assessment and decision-making techniques. The purpose of the dissertation was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, safety performance decision-making tool, specific to large, collegiate Title 14 CFR Part 141 flight training organizations, to increase safety and aid in operational decision-making. The validated safety decision-making tool uses what-if scenarios to assess how changes to the controllable input variables impact the overall level of operational risk within an organization’s flight department.
Read moreCategories: Graduate
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Predicting General Aviation Accidents Using Machine Learning Algorithms
PI Bradley Baugh
CO-I Bruce Conway
Aviation safety management is implemented through reactive, proactive, and predictive methodologies. Unlike reactive and proactive safety, predictive safety can predict the next accident and enable prevention before an actual occurrence. The study outlined here promotes predictive safety management through machine learning technologies using large amounts of data to facilitate predictive modeling.
Read moreCategories: Graduate
1-2 of 2 results