Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (T_c) for complex oxides, and T_c values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.
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机译:Discussion of 'Maximum Gradient Decision-Making for Railways Based on Convolutional Neural Network' by Hao Pu, Hong Zhang, Paul Schonfeld, Wei Li, Jie Wang, Xianbao Peng, and Jianping Hu