By Topic

Fitness Function Optimized in Genetic Algorithm for Fabric Dynamic Simulation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Beibei Li ; Sch. of Electron. & Electron. Eng., Shanghai second Polytech. Univ., Shanghai, China ; Zhihong Zhao

This paper proposes an improved algorithm to optimize the fitness function, with which the iteration times can be efficiently reduced in simulating fabric pattern deformation when it flags in the wind. Relying on a genetic algorithm model used to its deformation, an iteration method is employed and performed when genes are substituted with positions and color values of each point on the fabric surface. Relations are found during optimization between variables of the fitness function and the fabric attributes. The optimization is performed and improved to enhance the simulation. The result occurs in effectively reducing the iteration times while the actual visual effect is still satisfactory.

Published in:

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on  (Volume:1 )

Date of Conference:

19-20 Dec. 2008