WebApr 13, 2024 · To guarantee data quality, variables with ⩾60% missing values were discarded. In our COVID-19 & Air Pollution Working Group, we considered of particular interest to study the influence of socioeconomic and air quality factors on the severity of COVID-19, also motivated by the growing evidence from the literature (Introduction). WebAir pollution is a global problem, and air pollution concentration assessment plays an essential role in evaluating the associated risk to human health. Unfortunately, air pollution monitoring stations often have periods of missing data. In this thesis, we investigated missing values problem in air quality data by looking at the hourly pollutant …
Imputation Method Based on Collaborative Filtering and Clustering …
Webbetween air pollutants and asthma e.g. [6], mortality e.g. [28] and morbidity e.g. [7]. The World Health Organization [26], estimated that 4.2 million premature deaths per year are linked to air pollution. The air pollutant concentrations that are used to determine the air qual-ity index in the UK are O3,NO2,SO2,PM10,andPM2.5. These are measured Web(Tanner and Wong 1987) or multiple imputation techniques (Rubin 1996). However, the success of any imputation method relies on specifying a model that best describes the conditional distribution of the missing data given the observed data. Often several plausible imputation models are available for prediction and missing data imputation. marilyn a green festus mo
Fuzzy-based missing value imputation technique for air pollution …
WebDec 11, 2024 · Another imputation method is k-means clustering imputation (KMI) . The k-means method partitions the records into k clusters, so that records inside each cluster are similar, while the cluster centroids are distant. ... Junninen H, Niska H, Tuppurainen K, Ruuskanen J, Kolehmainen M (2004) Methods for imputation of missing values in air … WebApr 1, 2024 · Existing methods on missing data either cannot effectively capture the temporal and spatial mechanism of air pollution or focus on sequences with low missing rates and random missing positions. To address this problem, this paper proposes a new imputation methodology, namely transferred long short-term memory-based iterative … WebJun 21, 2016 · Missing values are common in cyber-physical systems (CPS) for a variety of reasons, such as sensor faults, communication malfunctions, environmental interferences, and human errors. An accurate missing value imputation is crucial to promote the data quality for data mining and statistical analysis tasks. Unfortunately, most of the existing … marilyn adele ritchie