Cart (Loading....) | Create Account
Close category search window
 

Ensemble of Predictors for Forecasting the PM10 Pollution

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)

The paper presents the novel approach to the accurate forecasting of the daily average concentration of PM10. It is based on the application of neural networks and wavelet transformation of the time series representing PM10 pollution. The main novelty of the proposed approach is the application of the ensemble of predictors, integrated using the blind source separation method or neural based integration. The numerical experiments of predicting the daily concentration of the PM10 pollution in Warsaw have shown good overall accuracy of prediction in terms of RMSE, MAE and MAPE errors.

Published in:

Theoretical Engineering (ISTET), 2009 XV International Symposium on

Date of Conference:

22-24 June 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.