HIGHLIGHTS
- who: uff1a and colleagues from the PACSuff1a0230.Ikuff0c02.60.-xuff0c05.45.-a * This work is supported by National Natural Science Foundation of China under Grant Nos. , and, and K.C. Wong Magna Fund in Ningbo University. have published the paper: u68afu5ea6u4f18u5316u7269u7406u4fe1u606fu795eu7ecfu7f51u7edc (GOPINNs) uff1au6c42u89e3u590du6742u975eu7ebfu6027u95eeu9898u7684u6df1u5ea6 u5b66u4e60u65b9u6cd5, in the Journal: (JOURNAL)
- what: Although this model has good results in some nonlinear problems, it still has some shortcomings. The authors propose a gradient-optimized physics-informed neural_networks (GOPINNs) model in this paper, which proposes a new neural_network structure and balances the interaction between different terms in the loss function . . .
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