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SAFETY INDEX OF HEAT WAVE MORTALITY USING BIG DATA

机译:使用大数据的热波死亡率安全指标

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Safety-related research using big data is still in its early stage in Korea. Recently, we have tried to solve some safety-related problems using big data. In this research, we will attempt to solve heat wave-related death which is a significant potential concern associated with climate change. Although deaths from heat disorders are a direct effect of heat wave incidences, only a few studies have addressed the causal factors between heat wave incidences and deaths from heat disorder. Regression analysis is applied to deduce the causal factors that affect the number of deaths from heat disorders (NDHD) in South Korea by using time-series dataset, which are the NDHD and climate data. Both are observational data from 1994 to 2012, collected from the National Statistical Office and the Korean Meteorological Agency, respectively. As a result, the duration of a heat wave and the age of the population are highly correlated with the NDHD. Based on this correlation, we also analyze the safety index of heat wave mortality. The paper is structured as follows: First of all, it presents the data and methods, including our strategy for analysis of heat wave incidences based on observational and climate modeling datasets. The next section presents the results of regression models applied for predicting heat wave deaths in Korea and discusses the statistical analysis of the results.
机译:在韩国,使用大数据进行与安全相关的研究仍处于初期阶段。最近,我们尝试使用大数据解决一些与安全相关的问题。在这项研究中,我们将尝试解决与热浪有关的死亡,这是与气候变化相关的重大潜在隐患。尽管由热失调引起的死亡是热浪发病的直接影响,但只有少数研究解决了热浪发病与热失调死亡之间的因果关系。通过使用时间序列数据集(NDHD和气候数据),使用回归分析来推断影响韩国因热障碍(NDHD)死亡人数的因果因素。两者均为1994年至2012年的观测数据,分别从国家统计局和大韩民国气象厅收集。结果,热浪的持续时间和人口的年龄与NDHD高度相关。基于此相关性,我们还分析了热浪死亡率的安全指数。本文的结构如下:首先,它介绍了数据和方法,包括我们基于观测和气候建模数据集分析热浪事件的策略。下一部分介绍了用于预测韩国热浪死亡的回归模型的结果,并讨论了结果的统计分析。

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