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K-Clustering Methods for Investigating Social-Environmental and Natural-Environmental Features Based on Air Quality Index
Victor Chang, Pin Ni, Yuming Li
Centre for Digital Innovation
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Article
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peer-review
1
Citation (Scopus)
92
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Dive into the research topics of 'K-Clustering Methods for Investigating Social-Environmental and Natural-Environmental Features Based on Air Quality Index'. Together they form a unique fingerprint.
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Keyphrases
Natural Environmental
100%
Feature-based
100%
Clustering Methods
100%
Environmental Features
100%
K-clustering
100%
Air Quality Index
100%
Environmental Hazards
50%
China
50%
Health Hazards
50%
Air Pollution
50%
AI-based Methods
50%
Data Analysis Methods
50%
Data-centric
50%
Artificial Intelligence Algorithm
50%
Big Data Techniques
50%
Data Processing Techniques
50%
Processing Analysis
50%
Performance Accuracy
50%
Data Visualization Techniques
50%
Air Quality Data
50%
Computer Science
Clustering Method
100%
Artificial Intelligence
100%
Analysis Technique
50%
Visualization Technique
50%
Big Data Technique
50%
Scientific Visualization
50%
Data Processing
50%
Air Pollution
50%
Earth and Planetary Sciences
Scientific Visualization
33%