Prediction of Air Quality from PM10 Concentrations and Meteorological Information Using Cross-Data Analytics
Jun 30, 2023·
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0 min read
Muhammed ŞARA
Süleyman Eken (Advisor)
Abstract
Increasing air pollution with our developing world affects our lives negatively.
This thesis proposes a cross-data analytics approach to estimate air quality from PM10 concentrations and meteorological information.
Using datasets from Asian regions and the MediaEval “Insight for Wellbeing” benchmark, multiple machine learning models were examined and results were visualized to infer regional air quality indices.
This thesis proposes a cross-data analytics approach to estimate air quality from PM10 concentrations and meteorological information.
Using datasets from Asian regions and the MediaEval “Insight for Wellbeing” benchmark, multiple machine learning models were examined and results were visualized to infer regional air quality indices.
Type
Publication
M.Sc. Thesis, Kocaeli University, Graduate School of Natural and Applied Sciences
