基于BP人工神经网络的船舶驾驶疲劳评价研究

Qing Liu, Zhifeng Li
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引用次数: 4

摘要

驾驶员疲劳是导致恶性事故发生的重要原因,对船舶驾驶员疲劳进行评估,减少驾驶员疲劳造成的事故具有重要的现实意义。在综合分析驾驶员驾驶疲劳影响因素的基础上,提出了以驾驶员闭眼时间、视线跳动频率、瞳孔直径大小为3个指标的船舶驾驶疲劳评价方法,建立了基于BP人工神经网络的船舶驾驶疲劳评价模型。最后,结合基于眼动仪SMI iView X HED的实验,对评价模型进行了验证和分析。本文为船舶驾驶疲劳评价提供了一种可行的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation studies on ship driving fatigue based on BP artificial neural network
Driver fatigue is an important reason that leads to a vicious accident, it has important practical significance to evaluate the ship driver's fatigue and reduce accidents caused by driver fatigue. On the basis of a comprehensive analysis of the factors that influenced driving fatigue, the paper proposed an evaluation on ship driving fatigue which using driver eye's closure time, the beat frequency of sight line, pupil diameter size as 3 indicators, building the evaluation model based on BP artificial neural network. Finally, combining with the experiment based on eye tracker SMI iView X HED, it verifies and analyses the evaluation model. The paper provides a feasible method for the evaluation on ship driving fatigue.
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