Article
Effect of HFACS and non-HFACS-related factors on fatalities in general aviation accidents using neural networks.
USF St. Petersburg campus Faculty Publications
Document Type
Article
Publication Date
2013
Abstract
This study applied a backpropagation artificial neural network approach to investigate both the Human Factors Analysis and Classification System (HFACS)-related unsafe act tiers of factors and other non-HFACS factors in an attempt to recognize patterns for general aviation accident fatalities. Data were obtained from the HFACS database and extracted from the National Transportation Safety Board database from 1990 to 2002. Multiple neural network models were created and the best fit model was selected based on a sequence of criteria. A sensitivity analysis was performed on the validated model to rank the factors that lead to general aviation fatalities. Results are discussed and practical implications are given.
Publisher
Taylor & Francis
Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 4.0
Citation Information
Liu, D., Nickens, T., Hardy, L., & Boquet, A. (2013). Effect of HFACS and non-HFACS-related factors on fatalities in general aviation accidents using neural networks. International Journal of Aviation Psychology, 23(2), 153-168. doi:10.1080/10508414.2013.772831
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