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

Daily rainfall forecasting using an ensemble technique based on singular spectrum analysis

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

4 Author(s)
Masulli, F. ; Dipartimento di Inf. e Sci. dell''Inf., Genoa Univ., Italy ; Baratta, D. ; Cicioni, G. ; Studer, L.

Studer and Masulli (1995), Masulli, Parenti, and Studer (1999), and Masulli, Cicione, and Studer (2000) proposed a constructive methodology for temporal data learning supported by results and prescriptions related to the Takens-Mane theorem and using the singular spectrum analysis in order to reduce the effects of the possible discontinuity of the signal. In this paper we present some new results concerning the application of this approach to the forecasting of the individual rainfall intensities series collected by 135 stations distributed in the Tiber basin

Published in:

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on  (Volume:1 )

Date of Conference:

2001

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.