近5年高被引文献
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems
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OpenAlex
572
FWCI65.875
A MTPA and Flux-Weakening Curve Identification Method Based on Physics-Informed Network Without Calibration
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OpenAlex
288
FWCI13.5219
Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
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FWCI43.1547
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
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262
FWCI30.25
A novel sequential method to train physics informed neural networks for Allen Cahn and Cahn Hilliard equations
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OpenAlex
226
FWCI26.1314
A physics-informed neural network technique based on a modified loss function for computational 2D and 3D solid mechanics
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213
FWCI24.125
Physics-informed Neural Networks (PINN) for computational solid mechanics: Numerical frameworks and applications
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FWCI55.0762
Can physics-informed neural networks beat the finite element method?
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OpenAlex
153
FWCI40.2482
Synchronous Reluctance Machines: A Comprehensive Review and Technology Comparison
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OpenAlex
147
FWCI13.2737
A physics-informed neural network approach to fatigue life prediction using small quantity of samples
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OpenAlex
133
FWCI15.387