Abstract
This paper presents a new divide-and-conquer learning approach to radial basis function networks (DCRBF). The DCRBF network is a hybrid system consisting of several sub-RBF networks, each of which takes a sub-input space as its input. Since this system divides a high-dimensional modeling problem into several low-dimensional ones, it can considerably reduce the structural complexity of a RBF network, whereby the net's learning becomes much faster. We have empirically shown its outstanding learning performance on forecasting two real time series as well as synthetic data in comparison with a conventional RBF one.
Original language | English |
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Title of host publication | Intelligent Data Engineering and Automated Learning |
Subtitle of host publication | 4th International Conference, IDEAL 2003 Hong Kong, China, March 21–23, 2003 Revised Papers |
Editors | Jiming Liu, Yiu-ming Cheung, Hujun Yin |
Place of Publication | Berlin, Heidelberg |
Publisher | Springer |
Pages | 143-150 |
Number of pages | 8 |
Edition | 1st |
ISBN (Electronic) | 9783540450801 |
ISBN (Print) | 9783540405504 |
DOIs | |
Publication status | Published - 29 Jul 2003 |
Event | 4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003 - Hong Kong Convention and Exhibition Centre, Hong Kong, China Duration: 21 Mar 2003 → 23 Mar 2003 https://link.springer.com/book/10.1007/b11717 http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference website) http://www.comp.hkbu.edu.hk/IDEAL2003/ (conference program) |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 2690 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Name | International Conference on Intelligent Data Engineering and Automated Learning |
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Conference
Conference | 4th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2003 |
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Country/Territory | China |
City | Hong Kong |
Period | 21/03/03 → 23/03/03 |
Internet address |
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Scopus Subject Areas
- Theoretical Computer Science
- General Computer Science
User-Defined Keywords
- Independent Component Analysis
- Principle Component Analysis
- Radial Basis Function Network
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