By Topic

Nonlinear time series modelling and prediction using Gaussian RBF network with evolutionary structure optimisation

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

4 Author(s)
Sun-Gi Hong ; Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea ; Sang-Keon Oh ; Min-Soeng Kim ; Ju-Jang Lee

An evolutionary structure optimisation method for the Gaussian radial basis function network is presented for modelling and predicting nonlinear time series. The generalisation performance is significantly improved with a much smaller network, compared with that of the previous clustering and least square learning method

Published in:

Electronics Letters  (Volume:37 ,  Issue: 10 )