Curve and surface constructions using rational B-splines
Computer-Aided Design
Trends in curve and surface design
Computer-Aided Design
Curve and surface fitting with splines
Curve and surface fitting with splines
The NURBS book
Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems
From Conics to NURBS: A Tutorial and Survey
IEEE Computer Graphics and Applications
Capturing Outline of Fonts Using Genetic Algorithm and Splines
IV '01 Proceedings of the Fifth International Conference on Information Visualisation
An Artificial Immune System Approach for B-Spline Surface Approximation Problem
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Automatic knot adjustment using an artificial immune system for B-spline curve approximation
Information Sciences: an International Journal
Information Sciences: an International Journal
Hi-index | 0.00 |
In curve fitting problems, the selection of knots in order to get an optimized curve for a shape design is well-known. For large data, this problem needs to be dealt with optimization algorithms avoiding possible local optima and at the same time getting to the desired solution in an iterative fashion. Many evolutionary optimization techniques like genetic algorithm, simulated annealing have already been successfully applied to the problem. This paper presents an application of another evolutionary heuristic technique known as “Simulated Evolution” (SimE) to the curve fitting problem using NURBS. The paper describes the mapping scheme of the problem to SimE followed by the proposed algorithm's outline with the results obtained.