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Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction 被引量:2

Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction
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摘要 The equilibrium model for multicomponent rare earth extraction is developed using neural networks, which combined with the material balance model could give online prediction of component content in countercurrent rare earth (extraction) production. Simulation experiments with industrial operation data prove the effectiveness of the hybrid soft-(sensor). The equilibrium model for multicomponent rare earth extraction is developed using neural networks, which combined with the material balance model could give online prediction of component content in countercurrent rare earth (extraction) production. Simulation experiments with industrial operation data prove the effectiveness of the hybrid soft-(sensor).
出处 《Journal of Rare Earths》 SCIE EI CAS CSCD 2003年第6期691-696,共6页 稀土学报(英文版)
基金 ProjectsupportedbytheNationalTenthFive Year PlanofKeyTechnology (2 0 0 2BA3 15A)
关键词 countercurrent extraction first principle model soft-sensor model neural networks rare earths countercurrent extraction first principle model soft-sensor model neural networks rare earths
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