Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques-Reference-Cited by-同舟云学术

Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques

Published:2022-10-15 Issue:4 Volume:81 Page:591-613
ISSN:1018-4864
Container-title:Telecommunication Systems
language:en
Short-container-title:Telecommun Syst

Author:

Baqer Noor S.,Albahri A. S.,Mohammed Hussein A.,Zaidan A. A.^ORCID,Amjed Rula A.,Al-Bakry Abbas M.,Albahri O. S.,Alsattar H. A.,Alnoor Alhamzah,Alamoodi A. H.,Zaidan B. B.,Malik R. Q.,Kareem Z. H.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11235-022-00959-2.pdf

Reference88 articles.

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2. U. S. E. P. Agency and I. Division (2014). Air Quality Index (AQI). Encycl. Qual. Life Well-Being Res., no. February, pp. 120–120. Doi: https://doi.org/10.1007/978-94-007-0753-5_100115.

3. Pitarma, R., Marques, G., & Ferreira, B. R. (2017). Monitoring indoor air quality for enhanced occupational health. Journal of Medical Systems, 41(2), 23. https://doi.org/10.1007/s10916-016-0667-2

4. Thomas, N. M., et al. (2019). Investigation of indoor air quality determinants in a field study using three different data streams. Building and Environment, 154, 281–295. https://doi.org/10.1016/j.buildenv.2019.03.022

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