Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/725
Title: B-Spline Curve Approximation by Utilizing Big Bang-Big Crunch Method
Authors: İnik, Özkan
Ülker, Erkan
Koç, İsmail
Keywords: B-Spline curve fitting
Big Bang-Big Crunch
Knot placement
Reverse engineering
ALGORITHM
Publisher: TECH SCIENCE PRESS
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.
URI: https://hdl.handle.net/20.500.13091/725
ISSN: 0267-6192
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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