Evolving mixture of experts for nonlinear time series modelling and prediction

The evolutionary structure optimisation (ESO) method for Gaussian radial basis function (RBF) networks has already been presented by the authors. Here, they improve the ESO method in its mutation operator and apply it to a mixture of experts (ME) for modelling and predicting nonlinear time series. The ME implementation provides much better generalisation performance with fewer network parameters, compared to the Gaussian RBF networks.
Publisher
IEE-INST ELEC ENG
Issue Date
2002-01
Language
ENG
Citation

ELECTRONICS LETTERS, v.38, no.1, pp.34 - 35

ISSN
0013-5194
URI
http://hdl.handle.net/10203/8281
Appears in Collection
EE-Journal Papers(저널논문)
  • Hit : 175
  • Download : 1
  • Cited 0 times in thomson ci
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡClick to seewebofscience_button
⊙ Cited 1 items in WoSClick to see citing articles inrecords_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0