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Reliability estimation of neural networks with human factors under emergency of nuclear power plant

机译:核电厂紧急情况下人为因素的神经网络的可靠性估计

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Recently, people do not pay attention to the events arised from human factors until human factors events occur more and more frequent. In this paper, the authors take nuclear power plant as reference background and propose a particular neural network model for emergency with human factors. The model comprises of three assessment parts. For each part, the authors come up with specific function in order to assess human factors error probability of emergency. The proposed methods are tested by experiments. From results of experiments, we can easily see that human factors error probability is precise and reliable in the model, that the proposed method is more accurate than a single weibull function, that which active function is better, and that which tolerance is minimum. The method can be applied to human factors reliability analysis in emergency of nuclear power plant and has a great significance for safety accidents in nuclear power plant.
机译:近年来,人们不再关注由人为因素引起的事件,直到人为因素事件发生的频率越来越高。在本文中,作者以核电站为参考背景,并提出了一种特殊的人为因素引起的神经网络模型。该模型包括三个评估部分。对于每个部分,作者提出特定的功能,以评估人为因素导致紧急情况的错误概率。通过实验对提出的方法进行了测试。从实验结果可以很容易地看出,人为因素在模型中的错误概率是准确可靠的,所提出的方法比单一的威布尔函数更精确,哪个主动函数更好,容差最小。该方法可用于核电厂紧急情况下的人为因素可靠性分析,对核电厂安全事故具有重要意义。

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