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ARTICLE
B-Spline Curve Approximation by Utilizing Big Bang-Big Crunch Method
Özkan inik1,∗, Erkan Ülker2, ismail Koç2
1 Department of Computer Engineering, Gaziosmanpa¸sa University, Tokat, Turkey
2 Department of Computer Engineering, Konya Technical University, Konya, Turkey
* Corresponding Author:Özkan inik,
Computer Systems Science and Engineering 2020, 35(6), 431-440. https://doi.org/10.32604/csse.2020.35.431
Abstract
The location of knot points and estimation of the number of knots are undoubtedly known as one of the most difficult problems in B-Spline curve
approximation. In the literature, different researchers have been seen to use more than one optimization algorithm in order to solve this problem. In this
paper, Big Bang-Big Crunch method (BB-BC) which is one of the evolutionary based optimization algorithms was introduced and then the approximation
of B-Spline curve knots was conducted by this method. The technique of reverse engineering was implemented for the curve knot approximation. The
detection of knot locations and the number of knots were randomly selected in the curve approximation which was performed by using BB-BC method.
The experimental results were carried out by utilizing seven different test functions for the curve approximation. The performance of BB-BC algorithm was
examined on these functions and their results were compared with the earlier studies performed by the researchers. In comparison with the other studies, it
was observed that though the number of the knot in BB-BC algorithm was high, this algorithm approximated the B-Spline curves at the rate of minor error.
Keywords
Cite This Article
. Inik, E. Ülker and I. Koç, "B-spline curve approximation by utilizing big bang-big crunch method,"
Computer Systems Science and Engineering, vol. 35, no.6, pp. 431–440, 2020. https://doi.org/10.32604/csse.2020.35.431