Abstract
In this paper we construct a novel evolutionary algorithm. It yields good performance on a collection of parabolic parameter identification problems. The algorithm has a good tolerability for the noise in the observed data. Even when the noise level is up to 10% we can also get such a good result.
This work was supported by Open Fund of State Key Laboratory of Software Engineering, Wuhan University, National Natural Science Foundation of China (Nos. 60133010, 60073043, 70071042)
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© 2004 Springer-Verlag Berlin Heidelberg
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Wu, Z., Tang, Z., Zou, J., Kang, L., Li, M. (2004). An Evolutionary Algorithm for Parameters Identification in Parabolic Systems. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_154
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DOI: https://doi.org/10.1007/978-3-540-24855-2_154
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22343-6
Online ISBN: 978-3-540-24855-2
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