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My bibliography Save this articleData-driven vector localized waves and parameters discovery for Manakov system using deep learning approach
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DOI: 10.1016/j.chaos.2022.112182
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References listed on IDEAS
- Wu, Gang-Zhou & Fang, Yin & Wang, Yue-Yue & Wu, Guo-Cheng & Dai, Chao-Qing, 2021. "Predicting the dynamic process and model parameters of the vector optical solitons in birefringent fibers via the modified PINN," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
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Cited by:
- Zhong, Ming & Yan, Zhenya, 2022. "Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
- Jaganathan, Meiyazhagan & Bakthavatchalam, Tamil Arasan & Vadivel, Murugesan & Murugan, Selvakumar & Balu, Gopinath & Sankarasubbu, Malaikannan & Ramaswamy, Radha & Sethuraman, Vijayalakshmi & Malomed, 2023. "Data-driven multi-valley dark solitons of multi-component Manakov Model using Physics-Informed Neural Networks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
- Fang, Yin & Zhu, Bo-Wei & Bo, Wen-Bo & Wang, Yue-Yue & Dai, Chao-Qing, 2023. "Data-driven prediction of spatial optical solitons in fractional diffraction," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
- Chen, Junchao & Song, Jin & Zhou, Zijian & Yan, Zhenya, 2023. "Data-driven localized waves and parameter discovery in the massive Thirring model via extended physics-informed neural networks with interface zones," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
- Yin, Yu-Hang & Lü, Xing, 2024. "Multi-parallelized PINNs for the inverse problem study of NLS typed equations in optical fiber communications: Discovery on diverse high-order terms and variable coefficients," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
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Keywords
Data-driven vector localized waves; Vector rogue waves; Parameters discovery; Manakov system; Improved PINN;All these keywords.
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