Article ID: | iaor1999872 |
Country: | Japan |
Volume: | 11 |
Issue: | 4 |
Start Page Number: | 198 |
End Page Number: | 207 |
Publication Date: | Apr 1998 |
Journal: | Transactions of the Institute of Systems, Control and Information Engineers |
Authors: | Kondo Tadashi |
Keywords: | heuristics, networks, organization |
A GMDH type neural network algorithm which can identify a nonlinear system whose structure is very complex is proposed. In this algorithm, the heuristic self-orgnization method of the GMDH algorithm is used and so a neural network structure which has a good prediction accuracy can be organized automatically. Furthermore, instead of the partial polynomials which are used in the GMDH algorithm, partial-neural networks which have four layered hierarchical network structures are used to construct the GMDH type neural network. The proposed algorithm is applied to a nonlinear system identification problem and its advantage over the GMDH algorithm and the conventional networks is shown.