Design optimization by functional neural networks

被引：1

作者：

Liu, XY ^{[1
]}

Duan, HC ^{[1
]}

Tang, MX ^{[1
]}

机构：

[1] Shandong Normal Univ, Sch Informat & Management, Shandong 250014, Peoples R China

来源：

PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, VOLS 1 AND 2 | 2005年

关键词：

partial ordering; cone; functional link; neural networks; learning algorithms;

D O I：

10.1109/CSCWD.2005.194292

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a new design optimization technique by artificial neural networks. Based on the theory of partial ordering and cones in Banach spaces, a new kind of neural networks with functional links is proposed Learning algorithm lies heavily on the ordering structure of the sample space with an alternative feed-forward and backpropagation technique. Experiments are described with comparison with traditional functional link networks and wavelet networks.

引用

页码：824 / 829

页数：6

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