ABSTRACT

Using statistical methods for categorical data analysis, namely multiple correspondence analysis and Artificial Intelligence through Bayesian networks, we analysed a database of occupational mining accidents for Spain for the period 2004–2017 to identify the factors most associated with the occurrence of fatal and non-fatal accidents. The results obtained allow to shed light on the hidden patterns present in different work situations where accidents can have fatal consequences. In addition, this study exemplifies the application of statistical techniques suitable for Big Data and data-driven decision making in the mining sector.

中文翻译：

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使用人工智能技术区分致命和非致命采矿事故

摘要

我们使用统计方法进行分类数据分析，即多重对应分析和通过贝叶斯网络的人工智能，我们分析了西班牙2004-2017年职业采矿事故数据库，以确定与致命和非致命事故发生最相关的因素事故。所获得的结果可以揭示在不同的工作环境中存在的隐藏模式，在这些情况下事故可能会造成致命的后果。此外，本研究还举例说明了适用于采矿业中大数据和数据驱动决策的统计技术的应用。