Shape reconstruction by genetic algorithms and artificial neural networks

被引：8
|
作者：
Liu, XY [1 ]
Tang, MX [1 ]
Frazer, JH [1 ]
机构：
[1] Hong Kong Polytech Univ, Sch Design, Design Technol Res Ctr, Kowloon, Hong Kong, Peoples R China
来源：
ENGINEERING COMPUTATIONS | 2003年 / 20卷 / 1-2期
关键词：
neural networks; genetic algorithms; model; design;
D O I：
10.1108/02644400310465281
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents a new surface reconstruction method based on complex form functions, genetic algorithms and neural networks. Surfaces can be reconstructed in an analytical representation format This representation is optimal in the sense of least-square fitting by predefined subsets of data points. The surface representations are achieved by evolution via repetitive application of crossover and mutation operations together with a back-propagation algorithm until a termination condition is met The expression is finally classified into specific combinations of basic functions. The proposed method can be used for CAD model reconstruction of 3D objects and free smooth shape modelling. We have implemented the system demonstration with Visual C++ and MatLab to enable real time surface visualisation in the process of design.
引用
收藏
页码：129 / 151
页数：23
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