B-spline curve fitting with invasive weed optimization
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCIENCE INC
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
B-spline curves and surfaces are generally used in computer aided design (CAD), data visualization, virtual reality, surface modeling and many other fields. Especially, data fitting with B-splines is a challenging problem in reverse engineering. In addition to this, B-splines are the most preferred approximating curve because they are very flexible and have powerful mathematical properties and, can represent a large variety of shapes efficiently [1]. The selection of the knots in B-spline approximation has an important and considerable effect on the behavior of the final approximation. Recently, in literature, there has been a considerable attention paid to employing algorithms inspired by natural processes or events to solve optimization problems such as genetic algorithms, simulated annealing, ant colony optimization and particle swarm optimization. Invasive weed optimization (IWO) is a novel optimization method inspired from ecological events and is a phenomenon used in agriculture. In this paper, optimal knots are selected for B-spline curve fitting through invasive weed optimization method. Test functions which are selected from the literature are used to measure performance. Results are compared with other approaches used in B-spline curve fitting such as Lasso, particle swarm optimization, the improved clustering algorithm, genetic algorithms and artificial immune system. The experimental results illustrate that results from IWO are generally better than results from other methods. (C) 2017 Elsevier Inc. All rights reserved.
Açıklama
Anahtar Kelimeler
Invasive weed optimization, Weed colony, B-spline curves, Knot selection, Curve fitting, Reverse engineering
Kaynak
APPLIED MATHEMATICAL MODELLING
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
52
