A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neu...A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neural network principles. The nonlinearmapping between CE of LATE and various electrolytic conditions was obtained from a number of experimental data and used to predictCE of LATE. The trsined neural networks possessed high precision and resulted in a good predicting effect. As a result, attificial neuralnetworks as a new cooperating and predicting technology provide a new approach to the further studies on low temperature aluminumelectrolysis.展开更多
文摘A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neural network principles. The nonlinearmapping between CE of LATE and various electrolytic conditions was obtained from a number of experimental data and used to predictCE of LATE. The trsined neural networks possessed high precision and resulted in a good predicting effect. As a result, attificial neuralnetworks as a new cooperating and predicting technology provide a new approach to the further studies on low temperature aluminumelectrolysis.
