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- Zhejiang UniversityCN8 papers
- Zhejiang University of Science and TechnologyCN5 papers
- Jiyang College of Zhejiang A&F UniversityCN4 papers
- Zhejiang Academy of ForestryCN4 papers
- Zhejiang LabCN4 papers
- Zhejiang University of TechnologyCN4 papers
- Chinese Academy of SciencesCN3 papers
- Tel Aviv UniversityIL3 papers
- University of MichiganUS3 papers
- University of TarapacáCL3 papers
- Anna Needs Neuroblastoma AnswersUS2 papers
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4 papers · 1 filter
Predicting nonlinear dynamics of optical solitons in optical fiber via the SCPINN
Yin Fang, Wen-Bo Bo, Ru-Ru Wang +2
The strongly-constrained physics-informed neural network (SCPINN) is proposed by adding the information of compound derivative embedded into the soft-constraint of physics-informed…
Data-driven soliton solutions and model parameters of nonlinear wave models via the conservation-law constrained neural network method
Yin Fang, Gang-Zhou Wu, Yue-Yue Wang +1
In the process of the deep learning, we integrate more integrable information of nonlinear wave models, such as the conservation law obtained from the integrable theory, into the n…
Predicting the dynamic process and model parameters of the vector optical solitons in birefringent fibers via the modified PINN
Gang-Zhou Wu, Yin Fang, Yue-Yue Wang +2
A modified physics-informed neural network is used to predict the dynamics of optical pulses including one-soliton, two-soliton, and rogue wave based on the coupled nonlinear Schrö…
Data-driven femtosecond optical soliton excitations and parameters discovery of the high-order NLSE using the PINN
Yin Fang, Gang-Zhou Wu, Yue-Yue Wang +1
We use the physics-informed neural network to solve a variety of femtosecond optical soliton solutions of the high order nonlinear Schrödinger equation, including one-soliton solut…