K-Clustering Methods for Investigating Social-Environmental and Natural-Environmental Features Based on Air Quality Index

Victor Chang, Pin Ni, Yuming Li

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
6 Downloads (Pure)

Abstract

Air pollution has caused environmental and health hazards across the globe, particularly in emerging countries such as China. In this article, we propose the use of air quality index and the development of advanced data processing, analysis, and visualization techniques based on the AI-based k-clustering method. We analyze the air quality data based on seven key attributes and discuss its implications. Our results provide meaningful values and contributions to the current research. Our future work will include the use of advanced AI algorithms and big data techniques to ensure better performance, accuracy and real-time checks.

Original languageEnglish
Article number9143256
Pages (from-to)28-34
Number of pages7
JournalIT Professional
Volume22
Issue number4
DOIs
Publication statusPublished - 1 Jul 2020

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