@article{ref1,
title="Evaluating flight crew performance by a Bayesian network model",
journal="Entropy (Basel, Switzerland)",
year="2018",
author="Chen, Wei and Huang, Shuping",
volume="20",
number="3",
pages="e20030178-e20030178",
abstract="Flight crew performance is of great significance in keeping flights safe and sound. When evaluating the crew performance, quantitative detailed behavior information may  not be available. The present paper introduces the Bayesian Network to perform  flight crew performance evaluation, which permits the utilization of  multidisciplinary sources of objective and subjective information, despite sparse  behavioral data. In this paper, the causal factors are selected based on the  analysis of 484 aviation accidents caused by human factors. Then, a network termed  Flight Crew Performance Model is constructed. The Delphi technique helps to gather  subjective data as a supplement to objective data from accident reports. The  conditional probabilities are elicited by the leaky noisy MAX model. Two ways of  inference for the BN-probability prediction and probabilistic diagnosis are used and  some interesting conclusions are drawn, which could provide data support to make  interventions for human error management in aviation safety.<p /> <p>Language: en</p>",
language="en",
issn="1099-4300",
doi="10.3390/e20030178",
url="http://dx.doi.org/10.3390/e20030178"
}