Abstract
Curve fitting has many applications in lots of domains. The literature is full of fitting methods which are suitable for specific kinds of problems. In this paper we introduce a more general method to cover more range of problems. Our goal is to fit some cubic Bezier curves to data points of any distribution and order. The curves should be good representatives of the points and be connected and smooth. Theses constraints and the big search space make the fitting process difficult. We use the good capabilities of the coevolutionary algorithms in large problem spaces to fit the curves to the clusters of the data. The data are clustered using hierarchical techniques before the fitting process.
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Afshar, N.A., Soryani, M., Rahmani, A.T. (2011). Curve Fitting Using Coevolutionary Genetic Algorithms. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_24
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DOI: https://doi.org/10.1007/978-3-642-27242-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27241-7
Online ISBN: 978-3-642-27242-4
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