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Data Modeling Using NURBs Curves and Modified Genetic Algorithms

[+] Author Affiliations
Christopher Hammond, Cameron J. Turner

Colorado School of Mines, Golden, CO

Paper No. IMECE2010-37459, pp. 1089-1098; 10 pages
doi:10.1115/IMECE2010-37459
From:
  • ASME 2010 International Mechanical Engineering Congress and Exposition
  • Volume 3: Design and Manufacturing, Parts A and B
  • Vancouver, British Columbia, Canada, November 12–18, 2010
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4427-4
  • Copyright © 2010 by ASME

abstract

Non-Uniform Rational B-Splines (NURBS) curves have long been used to model 1D and 2D data because they are efficient to calculate, easy to manipulate, and capable of handling discontinuities and drastic changes in the general topology of the data. However, the user must assist in defining the control points, weights, knots and an order for the curve in order to fit the curve to the data. This paper uses a modified Genetic Algorithm (GA) to choose and manipulate these various parameters to produce a NURBS curve that minimizes the error between the data and the curve and also minimizes the time it takes the algorithm to compute the solution. The algorithm is tested on several 1D trial data sets and the results are explained. Then, several general difficulties for this application of the GA are explained and possible methods for overcoming them are discussed.

Copyright © 2010 by ASME

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