OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM

Acta Metall Sin

1995, Vol. 31

Issue (18): 284-288 DOI:

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OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM

ZHA NG Peixin; ZHA NG Qizhi; W U Liming; SUI Zhitong(Northeasiern Unirersity.Shenyang 110006)

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ZHA NG Peixin; ZHA NG Qizhi; W U Liming; SUI Zhitong(Northeasiern Unirersity.Shenyang 110006). OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM. Acta Metall Sin, 1995, 31(18): 284-288.

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Abstract

The relation among the MgO-B2O3-SiO2 slag compositions and the efficiencies of extraction of B has been fitted and predicated by artificial neural network. The optimum composition corresponding to the highest efficiency of extraction of B was obtained using genetic algorithm. It is believed that the artificial neural network and genetic algorithm may provide a new and effective way for fitting and optimizing the process of extraction of B.

Key words: : artificial neural network genetic algorithm optimization of composition boron MgO-B_2O_3 SiO_2 slag

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https://www.ams.org.cn/EN/ OR https://www.ams.org.cn/EN/Y1995/V31/I18/284

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