Crystal property prediction and classification method based on attention mechanism and crystal graph volume neural network
A neural network and classification method technology, applied in the field of crystal property prediction and classification, can solve the problems of reduced prediction accuracy, reduced prediction model accuracy, and influence on network fitting, achieving the goal of less time-consuming, improved prediction and classification accuracy Effect
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[0061] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these embodiments are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention Modifications in equivalent forms all fall within the scope defined by the appended claims of this application.
[0062] The present invention provides a method for predicting and classifying crystal properties based on the attention mechanism and crystal map volume neural network, which is mainly divided into two stages: prediction of crystal properties and classification of crystal properties. In the first stage, mean square loss is used as the loss function , using stochastic gradient descent as the optimizer to predict the formation energy, absolute energy, bandgap and Fermi ener...
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