Missing Values Interpolation in PurpleAir Sensor Data based on a Correlation with Neighboring Locations using KNIME Analytics Platform

S. Omanovic, A. Midzic, Z. Avdagić, Damir Pozderac, Amel Toroman
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Abstract

Missing values handling in any collected data is one of the first issues that must be resolved to be able to use that data. This paper presents an approach used for missing values interpolation in PurpleAir particle pollution sensor data, based on a correlation of the measurements from the observed locations with the measurements from its neighboring locations, using KNIME Analytics Platform. Results of our experiments with data from five locations in Bosnia & Herzegovina, presented in this paper, show that this approach, which is relatively simple to implement, gives good results. All modeling and experiments were conducted using KNIME Analytics Platform.
基于KNIME分析平台的基于邻近位置相关性的PurpleAir传感器数据缺失值插值
任何收集到的数据中的缺失值处理是必须解决的首要问题之一,以便能够使用该数据。本文提出了一种利用KNIME分析平台,基于观测位置与邻近位置测量值的相关性,对PurpleAir颗粒污染传感器数据进行缺失值插值的方法。我们对波斯尼亚和黑塞哥维那五个地点的数据进行了实验,结果表明,这种方法相对简单,实施起来效果很好。所有建模和实验均使用KNIME分析平台进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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