Neural-network-based integrated model for predicting burn-through point in lead–zinc sintering process

Author:

Wu Min,Xu Chenhua,She Jinhua,Cao Weihua

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering

Reference32 articles.

1. Experimental study of phase equilibria in the PbO–ZnO–“Fe2O3”–(CaO + SiO2) system in air for the lead and zinc blast furnace sinters (CaO/SiO2 weight ratio of 0.933 and PbO/(CaO+SiO2) ratios of 2.0 and 3.2);Jak;Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science,2003

2. Reaction sintering of lead zinc niobate–lead zirconate titanate ceramics;Lee;Journal of the European Ceramic Society,2006

3. Prediction system of burning through point (BTP) based on adaptive pattern clustering and feature map;Cheng,2006

4. Peak bed temperature prediction on a lead/zinc sinter plant;Siemon;Minerals Engineering,1991

5. An application of adaptive genetic-neural algorithm to sinter's BTP process;Cheng,2004

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