Share Email Print

Proceedings Paper

Parametric design by learning
Author(s): Yonghua Chen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Parametric design is an effective and productive tool for the definition and modification of geometric models. This paper presents an intelligent method for the creation of a parametric model. In the proposed method, an adaptive neural network model is built to map the set of dimensional parameters to a set of coordinates. Defining a parametric model is equivalent to teaching the neural network. The user needs only specify a set of dimensional parameters that defines the parametric model and teach the neural network how to react to the changes of the dimensional parameters. Once the neural net work is taught, any dimensional changes will result in corresponding coordinate changes. This novel method eliminate the need of programming or graphic interaction that are normally required by contemporary parametric design systems.

Paper Details

Date Published: 22 March 1996
PDF: 7 pages
Proc. SPIE 2644, Fourth International Conference on Computer-Aided Design and Computer Graphics, (22 March 1996); doi: 10.1117/12.235581
Show Author Affiliations
Yonghua Chen, Univ. of Hong Kong (Hong Kong)

Published in SPIE Proceedings Vol. 2644:
Fourth International Conference on Computer-Aided Design and Computer Graphics
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

© SPIE. Terms of Use
Back to Top