Curve Fitting Using Conic by Evolutionary Computing
Zainor Ridzuan Yahya, Abd Rahni Mt Piah and Ahmad Abd Majid
DOI : 10.3844/jmssp.2012.107.110
Journal of Mathematics and Statistics
Volume 8, Issue 1
Problem statement: A direct method, such as least squares technique is usually used to solve problems involving matching a curve or a surface to a set of data points. The solution obtained by this direct method is precise or very good in approximation, but computationally not very efficient. Thus, in this study, we propose an indirect approach using Particle Swarm Optimization (PSO) technique as an alternative. Approach: As a case study, we use conic curve which satisfy C0 continuity to be fitted to a given set of data points. PSO, a soft computing method is employed to optimize the control points and weights which are then used in conic equations. Results: Best fitted conic curve that represents all the given data points is then obtained. Conclusion: We use an indirect technique of soft computing methods, i.e., PSO to fit a curve to a given data set. We believe that other types of soft computing based heuristic procedures may also be used to solve related problems or to find its effectiveness.
© 2012 Zainor Ridzuan Yahya, Abd Rahni Mt Piah and Ahmad Abd Majid. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.