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

authored by: 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.
Organisation(s): Geodetic Institute
Type: Article
Journal: Journal of Applied Geodesy
Volume: 13
Pages: 317-328
No. of pages: 12
ISSN: 1862-9016
Publication date: 25.10.2019
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Modelling and Simulation, Engineering (miscellaneous), Earth and Planetary Sciences (miscellaneous)
Electronic version(s): https://doi.org/10.1515/jag-2018-0015 (Access: Closed)
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