This Title All WIREs
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 7.250

Investigation of PM10 prediction utilizing data mining techniques: Analyze by topic

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Coarse particulate matter (PM10), the inhalable particles with an aerodynamic diameter smaller than 10 micrometers are one of the major air pollutions that affect human health. Over the previous decade, a number of researchers applied various data mining techniques to create a temporal prediction model. This study reviews and discusses 100 research articles in computer science and environmental science coming from the Scopus database. The three processes of data mining techniques, including data preparation, model creation, and model evaluation for prediction PM10 are highlighted. A summary of the overall process directions of data mining as well as their output are revealed. Additionally, recommendations for future research are identified. This article is categorized under: Application Areas > Science and Technology Technologies > Machine Learning Technologies > Prediction

Browse by Topic

Technologies > Prediction
Technologies > Machine Learning
Application Areas > Science and Technology

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts