Implementation of Speculate Modules and Performance Evaluation of Data Mining Clustering Techniques on Air Quality Index and Health Index to Predict High-Risk Air Polluted Stations of a Metropolitan City Using R Programming-Reference-Cited by-同舟云学术

Implementation of Speculate Modules and Performance Evaluation of Data Mining Clustering Techniques on Air Quality Index and Health Index to Predict High-Risk Air Polluted Stations of a Metropolitan City Using R Programming

Published:2021-07-31 Issue: Volume: Page:477-490
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Asha N.,Indira Gandhi M. P.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-1740-9_39

Reference14 articles.

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3. Sathya, D., Anu, J., Divyadharshini, M.: Air pollution analysis using clustering algorithms. In: 2017 International Conference on Emerging trends in Engineering, Science and Sustainable Technology (ICETSST). ISSN: 2348 – 8387

4. Govender, P., Sivakumar, V.: Application of K-means and Hierarchical clustering techniques for analysis of air pollution: a review (1980–2019). Elsevier vol. 11, Issue no. 1 (2019)

5. Doreswamy, Ghoneim, O.A., Manjaunath, B.R.: Air pollution clustering using K-means algorithm in smart city. Int. J. Innov. Res. Comput. Commun. Eng. 3(7) (2015)

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