ZHANG Qian, QIAO Dan, TANG Shaoqiang. DESIGNING ARTIFICIAL BOUNDARY CONDITIONS FOR ATOMIC CHAINS BY MACHINE LEARNING 1)[J]. MECHANICS IN ENGINEERING, 2020, 42(1): 13-16. DOI: 10.6052/1000-0879-19-412
Citation: ZHANG Qian, QIAO Dan, TANG Shaoqiang. DESIGNING ARTIFICIAL BOUNDARY CONDITIONS FOR ATOMIC CHAINS BY MACHINE LEARNING 1)[J]. MECHANICS IN ENGINEERING, 2020, 42(1): 13-16. DOI: 10.6052/1000-0879-19-412

DESIGNING ARTIFICIAL BOUNDARY CONDITIONS FOR ATOMIC CHAINS BY MACHINE LEARNING 1)

  • In this paper, we adopt machine learning techniques to design artificial boundary conditions for one-dimensional linear atomic chain. Training a feedforward neural network with a small amount of numerical solutions, we obtain artificial boundary conditions. This approach requires little prior information, and programming and computation are fast. Numerical examples illustrate a relatively small reflection.
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