Data mining methods for prediction of air pollution

DOI10.1515/AMCS-2016-0033zbMath1347.93048OpenAlexW2470363168MaRDI QIDQ326245

Krzysztof Siwek, Stanisław Osowski

Publication date: 12 October 2016

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/amcs-2016-0033

zbMATH Keywords

neural networkscomputational intelligencefeature selectionrandom forestair pollution forecasting

Mathematics Subject Classification ID

Ecology (92D40)

Related Items (1)

Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set

Uses Software

• Matlab
• foba

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Ensemble Neural Network Approach for Accurate Load Forecasting in a Power System
• 10.1162/153244303322753616
• A rainfall forecasting method using machine learning models and its application to the Fukuoka city case
• Random forests

This page was built for publication: Data mining methods for prediction of air pollution