Prediction Model of Smelting Endpoint of Fuming Furnace Based on Grey Neural Network

Song Qiang, WU Yaochun

Abstract


Since grey theory and neural network could improve prediction precision, the technology of combination prediction was proposed in this study. Then the algorithm was simulated by Matlab using practical data of a fuming furnace. The results reveal that the smelting endpoint of fuming furnace could be accurately predicted with this model by referring to small sample and information. Therefore, GNN model is effective with the advantages of high precision, fewer samples required and simple calculation.

Keywords


Smelting endpoint, gray neural network, prediction, sintering process, gray model

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DOI: http://dx.doi.org/10.12928/telkomnika.v14i3.3713

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TELKOMNIKA Telecommunication, Computing, Electronics and Control
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