Curve fitting with NURBS using simulated annealing

M. Sarfraz; M. Riyazuddin

doi:10.1007/3-540-31662-0_8

Curve fitting with NURBS using simulated annealing

M. Sarfraz^*
, M. Riyazuddin

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

12 Scopus citations

Abstract

The global optimization strategy of Simulated Annealing is applied to the optimization of knot parameters of NURBS for curve fitting, the objective being the reduction of fitting error to obtain a smooth curve. This is accomplished by using a unit weight vector and a fixed number of control points calculated using the least squares technique, while the sum of squared errors is taken as the objective function.

Original language	English
Title of host publication	Applied Soft Computing Technologies
Subtitle of host publication	The Challenge of Complexity
Editors	Ajith Abraham, Bernard Baets, Mario Koeppen, Bertram Nickolay
Pages	99-112
Number of pages	14
DOIs	https://doi.org/10.1007/3-540-31662-0_8
State	Published - 2006

Publication series

Name	Advances in Soft Computing
Volume	34
ISSN (Print)	1615-3871
ISSN (Electronic)	1860-0794

ASJC Scopus subject areas

Computer Science (miscellaneous)
Computational Mechanics
Computer Science Applications

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10.1007/3-540-31662-0_8

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abstract = "The global optimization strategy of Simulated Annealing is applied to the optimization of knot parameters of NURBS for curve fitting, the objective being the reduction of fitting error to obtain a smooth curve. This is accomplished by using a unit weight vector and a fixed number of control points calculated using the least squares technique, while the sum of squared errors is taken as the objective function.",

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AU - Riyazuddin, M.

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AB - The global optimization strategy of Simulated Annealing is applied to the optimization of knot parameters of NURBS for curve fitting, the objective being the reduction of fitting error to obtain a smooth curve. This is accomplished by using a unit weight vector and a fixed number of control points calculated using the least squares technique, while the sum of squared errors is taken as the objective function.

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SN - 3540316493

SN - 9783540316497

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A2 - Abraham, Ajith

A2 - Baets, Bernard

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Curve fitting with NURBS using simulated annealing

Abstract

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ASJC Scopus subject areas

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