UM
Forecasting time series using an artificial neural network with an instant learning and a stepwise updating algorithm
Chen C.L.Philip; Wan John Z.
1995-12-01
Source PublicationIntelligent Engineering Systems Through Artificial Neural Networks
Volume5
Pages759-763
AbstractWe propose a flat neural network model for time series forecasting and prediction applications. The flat neural network combined with nonlinear enhancement nodes allows us to predict and forecast nonlinear effect of different time series. A fast learning algorithm is utilized to find the optimal weights. A stepwise updating algorithm that updates the weight on-the-fly makes the system easy to import new observations while the system is running. The model is tested on several time-series data and the experiment results are compared with some existing models in which more complex architectures and more costly training are needed. Our results indicate that our model is very attractive to industrial monitoring process.
URLView the original
Language英語
Fulltext Access
Document TypeConference paper
CollectionUniversity of Macau
AffiliationWright State University
Recommended Citation
GB/T 7714
Chen C.L.Philip,Wan John Z.. Forecasting time series using an artificial neural network with an instant learning and a stepwise updating algorithm[C],1995:759-763.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen C.L.Philip]'s Articles
[Wan John Z.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen C.L.Philip]'s Articles
[Wan John Z.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen C.L.Philip]'s Articles
[Wan John Z.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.