Journal
EUROPEAN PHYSICAL JOURNAL PLUS
Volume 133, Issue 5, Pages -Publisher
SPRINGER HEIDELBERG
DOI: 10.1140/epjp/i2018-12013-3
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The aim of this study is to investigate the numerical treatment of the Painleve equation-II arising in physical models of nonlinear optics through artificial intelligence procedures by incorporating a single layer structure of neural networks optimized with genetic algorithms, sequential quadratic programming and active set techniques. We constructed a mathematical model for the nonlinear Painleve equation-II with the help of networks by defining an error-based cost function in mean square sense. The performance of the proposed technique is validated through statistical analyses by means of the one-way ANOVA test conducted on a dataset generated by a large number of independent runs.
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