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Air Quality Analysis Based on Outlier Detection Algorithms

Year: 2025

Type: article

Abstract: This study employs an outlier detection algorithm based on the distance metric of the Two-Step clustering algorithm to analyze potential untrustworthy data in pollutant concentration records across the region of Beijing-Tianjin-Hebei. By calculating anomaly indices through designated formulas and evaluating variable contribution rates, abnormal data points were identified for each monitoring area. Subsequent analysis of these anomalies provides substantial evidence supporting the existence of unreliable data within the dataset.

Source: Eurasia Journal of Science and Technology

DOI: 10.61784/ejst3083

Authors: QiZhi Zhang, Nan Jiang

Institution: Northeast Forestry University

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4410379082

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