Human Factors as Predictor of Fatalities in Aviation Accidents: A Neural Network Analysis

Abstract

In the area of aviation safety, the importance of human factors is indisputable. This research endeavors to assess the importance of human factors in predicting fatalities during aviation mishaps. Utilizing reports from the Aviation Safety Network Database, encompassing 1105 accidents and incidents spanning from 2007 to 2016, neural networks were trained to forecast the probability of fatalities. Our findings underscore that the human factors involved, by themselves, can yield strong predictions. As a term of comparison, other variables (type of occurrence, flight phase, and aircraft fate) were used as predictors, with poorer results; by combining these variables with human factors, the prediction is only marginally better, if at all, than that based on human factors alone. So, although these supplementary variables can marginally benefit the predictive results derived from human factors, their contribution remains minimal. Consequently, this study illuminates the paramount importance of human factors in influencing aviation fatalities, guiding stakeholders on the immediate interventions and investments which are most warranted to prevent them.

Keywords

• human factors
• aviation safety
• aviation fatalities
• aviation accidents
• neural networks
• prediction of fatalities