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)
