To read this content please select one of the options below:

$44.00 (excl. tax) 30 days to view and download

Shape reconstruction by genetic algorithms and artificial neural networks

Liu Xiyu, Tang Mingxi, John Hamilton Frazer

Engineering Computations

ISSN: 0264-4401

Article publication date: 1 March 2003

662

Abstract

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.

Keywords

Citation

Xiyu, L., Mingxi, T. and Hamilton Frazer, J. (2003), "Shape reconstruction by genetic algorithms and artificial neural networks", Engineering Computations, Vol. 20 No. 2, pp. 129-151. https://doi.org/10.1108/02644400310465281

Publisher

:

MCB UP Ltd

Copyright © 2003, MCB UP Limited

Related articles