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Fast converging elitist genetic algorithm for knot adjustment in B-spline curve approximation

verfasst von
Johannes Bureick, Hamza Alkhatib, Ingo Neumann
Abstract

B-spline curve approximation is a crucial task in many applications and disciplines. The most challenging part of B-spline curve approximation is the determination of a suitable knot vector. The finding of a solution for this multimodal and multivariate continuous nonlinear optimization problem, known as knot adjustment problem, gets even more complicated when data gaps occur. We present a new approach in this paper called an elitist genetic algorithm, which solves the knot adjustment problem in a faster and more precise manner than existing approaches. We demonstrate the performance of our elitist genetic algorithm by applying it to two challenging test functions and a real data set. We demonstrate that our algorithm is more efficient and robust against data gaps than existing approaches.

Organisationseinheit(en)
Geodätisches Institut
Typ
Artikel
Journal
Journal of Applied Geodesy
Band
13
Seiten
317-328
Anzahl der Seiten
12
ISSN
1862-9016
Publikationsdatum
25.10.2019
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Modellierung und Simulation, Ingenieurwesen (sonstige), Erdkunde und Planetologie (sonstige)
Elektronische Version(en)
https://doi.org/10.1515/jag-2018-0015 (Zugang: Geschlossen)
 

Details im Forschungsportal „Research@Leibniz University“