| Research Title |
Evolutionary training of a q-Gaussian radial basis functional-link nets for function approximation |
| Date of Distribution |
25 July 2013 |
| Conference |
| Title of the Conference |
10th International Joint Conference on Computer Science and Software Engineering (JCSSE) |
| Organiser |
Department of Computer Science, Faculty of Informatics, Mahasakham University |
| Conference Place |
Pullman Khon Kaen Raja Orchid hotel |
| Province/State |
Khonkaen, Thailand |
| Conference Date |
29 May 2013 |
| To |
31 May 2013 |
| Proceeding Paper |
| Volume |
2 |
| Issue |
1 |
| Page |
58-63 |
| Editors/edition/publisher |
|
| Abstract |
In this paper, radial basis functional-link nets (RBFLNs) based on a q-Gaussian function is proposed. In order to enhance the generalization performance of a modified radial basis function neural network and enhance the performance of the new network, the evolutionary algorithm named real-coded chemical reaction optimization (RCCRO), is presented for training the new network. A developed RCCRO, has been shown to perform well in many optimization problems. A RCCRO is employed to select the non-extensive entropic index q and the other parameters of the network. The experimental results of the function approximation show that the proposed approach can improve the performance of RBFLNs. |
| Author |
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| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
false |
| ใช้สำหรับสำเร็จการศึกษา |
ไม่เป็น |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
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Publication
Journal Publication
ไทย