Toward Air Quality Fuzzy Classification

Vagner Seibert, Rafael Bastos, Giovani Maia, Giancarlo Lucca, Helida Santos, Adenauer Yamin, Renata Reiser

2024

Abstract

This work considers different fuzzy classifier models to evaluate the air quality of indoor spaces, providing flexible systems related to the imprecision of metrics and parameters since the modeling process. Air Quality is a relevant topic concerning modern society, and the research on air quality evaluation provides important alternatives for improving global environmental governance. In this paper, we discuss the performances of the five fuzzy classifiers named CHI, FURIA, WF-C, FARC-HD, and SLAVE, applied in the data classification from an open dataset from Germany. Thus, this domain knowledge enables us to model the inherent uncertainties of attributes’ problems related to Air Quality and Air Quality Index. The results showed that fuzzy approaches offer a valid alternative for determining and correctly classifying indoor air quality with satisfying accuracy, adding flexible modeling in the air quality analysis.

Paper Citation

in Harvard Style

Seibert V., Bastos R., Maia G., Lucca G., Santos H., Yamin A. and Reiser R. (2024). Toward Air Quality Fuzzy Classification. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 771-778. DOI: 10.5220/0012689000003690

in Bibtex Style

@conference{iceis24,
author={Vagner Seibert and Rafael Bastos and Giovani Maia and Giancarlo Lucca and Helida Santos and Adenauer Yamin and Renata Reiser},
title={Toward Air Quality Fuzzy Classification},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={771-778},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012689000003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Toward Air Quality Fuzzy Classification
SN - 978-989-758-692-7
AU - Seibert V.
AU - Bastos R.
AU - Maia G.
AU - Lucca G.
AU - Santos H.
AU - Yamin A.
AU - Reiser R.
PY - 2024
SP - 771
EP - 778
DO - 10.5220/0012689000003690
PB - SciTePress