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Empirical verification for application of Bayesian inference in situation awareness evaluations

机译:贝叶斯推理在态势感知评估中应用的经验验证

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摘要

Bayesian methodology has been widely used in various research fields. According to current research, malfunctions of nuclear power plants can be detected using this Bayesian inference, which consistently piles up newly incoming data and updates the estimation. However, these studies have been based on the assumption that people work like computers perfectly a supposition that may cause a problem in real world applications. Studies in cognitive psychology indicate that when the amount of information to be processed becomes larger, people cannot save the whole set of data in their heads due to limited attention and limited memory capacity, also known as working memory.
机译:贝叶斯方法已被广泛用于各个研究领域。根据当前的研究,可以使用该贝叶斯推断来检测核电厂的故障,该推断始终堆积新输入的数据并更新估算值。但是,这些研究基于这样的假设:人们像计算机一样完美地工作,这可能会在现实世界的应用程序中引起问题。认知心理学研究表明,当要处理的信息量变大时,由于注意力有限和记忆容量有限(也称为工作记忆),人们无法将整个数据集保存在头脑中。

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