Prediction of Matte grade in Copper Flash Smelting Process based on LSTM and Mechanism Model
Author:
Affiliation:
1. Central South University,Changsha,China,410083
Funder
National Key R&D Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9901509/9901494/09902639.pdf?arnumber=9902639
Reference16 articles.
1. Time-series well performance prediction based on Long Short-Term Memory (LSTM) neural network model
2. Transductive LSTM for time-series prediction: An application to weather forecasting
3. Smelting Mechanism in the Reaction Shaft of a Commercial Copper Flash Furnace
4. Efficient Recovery of Copper and Cobalt from the Matte–Slag Mixture of ISA Furnace by Injection of Coke and Pyrite
5. Recovery of iron from copper flash smelting slags
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A data-driven soft-sensing model of matte grade in oxygen-rich side blow bath smelting process;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25
2. Prediction of matte grade in the oxygen-rich top blown smelting based on WD-SSA-SVM algorithm;2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS);2023-05-12
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