MM-AQI: A Novel Framework to Understand the Associations Between Urban Traffic, Visual Pollution, and Air Pollution

Tejima, Kazuki; Dao, Minh-Son; Zettsu, Koji

doi:10.1007/978-3-031-08530-7_50

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2024

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Cited by 2 publications

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Urban Visual Pollution Detection in Public Realm Using Artificial Intelligence: A Case Study of Riyadh Area, Saudi Arabia

Alzahrani,

Almutlaq

2024

Lecture Notes in Networks and Systems

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Urban Visual Pollution Detection in Public Realm Using Artificial Intelligence: A Case Study of Riyadh Area, Saudi Arabia

Alzahrani,

Almutlaq

2024

Lecture Notes in Networks and Systems

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The impact of data imputation on air quality prediction problem

Hua,

Nguyen,

Dao

et al. 2024

PLoS ONE

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With rising environmental concerns, accurate air quality predictions have become paramount as they help in planning preventive measures and policies for potential health hazards and environmental problems caused by poor air quality. Most of the time, air quality data are time series data. However, due to various reasons, we often encounter missing values in datasets collected during data preparation and aggregation steps. The inability to analyze and handle missing data will significantly hinder the data analysis process. To address this issue, this paper offers an extensive review of air quality prediction and missing data imputation techniques for time series, particularly in relation to environmental challenges. In addition, we empirically assess eight imputation methods, including mean, median, kNNI, MICE, SAITS, BRITS, MRNN, and Transformer, to scrutinize their impact on air quality data. The evaluation is conducted using diverse air quality datasets gathered from numerous cities globally. Based on these evaluations, we offer practical recommendations for practitioners dealing with missing data in time series scenarios for environmental data.

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MM-AQI: A Novel Framework to Understand the Associations Between Urban Traffic, Visual Pollution, and Air Pollution

Cited by 2 publications

References 20 publications

Urban Visual Pollution Detection in Public Realm Using Artificial Intelligence: A Case Study of Riyadh Area, Saudi Arabia

Urban Visual Pollution Detection in Public Realm Using Artificial Intelligence: A Case Study of Riyadh Area, Saudi Arabia

The impact of data imputation on air quality prediction problem

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