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

Rainfall intensity prediction by a spatial-temporal ensemble

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 $13
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

6 Author(s)
Tuan Zea Tan ; Inst. of High Performance Comput., Singapore ; Lee, G.K.K. ; Shie-Yui Liong ; Tian Kuay Lim
more authors

Accurate rainfall intensity nowcasting has many applications such as flash flood defense and sewer management. Conventional computational intelligence tools do not take into account temporal information, and the series of rainfall is treated as continuous time series. Unfortunately, rainfall intensity is not a continuous time series as it has different dry periods in between raining seasons. Hence, conventional computational intelligence tools sometimes are not able to offer acceptable accuracy. An ensemble constitutes of classification, regression and reward models is proposed. The classification model identifies rain or no rain episodes, whereas the regression model predicts the rainfall intensity. The error of the regression model is then predicted by the reward regression model. Through that, the spatial information is captured by the classification model, and the temporal information is captured by the regression and reward models. Preliminary experimental results are encouraging.

Published in:

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Date of Conference:

1-8 June 2008

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.