Deep learning neural networks for the third-order nonlinear Schrödinger equation: bright solitons, breathers, and rogue waves
نویسندگان
چکیده
The third-order nonlinear Schrodinger equation (alias the Hirota equation) is investigated via deep leaning neural networks, which describes strongly dispersive ion-acoustic wave in plasma and propagation of ultrashort light pulses optical fibers, as well broader-banded waves on water. In this paper, we use physics-informed networks (PINNs) learning method to explore data-driven solutions (e.g., soliton, breather, rogue waves) when two types unperturbated (a 2% noise) training data are considered. Moreover, PINNs study discovery parameters appearing with aid solitons.
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Article history: Received 13 April 2012 Received in revised form 13 October 2012 Accepted 26 October 2012 Available online 23 November 2012
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ژورنال
عنوان ژورنال: Communications in Theoretical Physics
سال: 2021
ISSN: ['0253-6102', '1572-9494']
DOI: https://doi.org/10.1088/1572-9494/ac1cd9