| 用神经网络─遗传算法优化MgO－B_2O_3─SiO_2渣系组成 |
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| 引用本文： | 张培新,张奇志,吴黎明,隋智通. 用神经网络─遗传算法优化MgO－B_2O_3─SiO_2渣系组成[J]. 金属学报, 1995, 31(18): 284-288 |
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| 作者姓名： | 张培新 张奇志 吴黎明 隋智通 |
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| 作者单位： | 东北大学 |
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| 摘 要： | 应用人工神经网络对ＭｇＯ－Ｂ_２Ｏ_３－ＳｉＯ_２渣系组成与硼提取率关系进行拟合和预测，首次采用遗传算法对组成优化，并得到最佳硼提取率所对应的组成。
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| 关 键 词： | 神经网络，遗传算法，组成，优化，MgO－B_2O_3－SiO_2渣系 |
OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM |
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| ZHA NG Peixin,ZHA NG Qizhi,W U Liming,SUI Zhitong. OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM[J]. Acta Metallurgica Sinica, 1995, 31(18): 284-288 |
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| Authors: | ZHA NG Peixin ZHA NG Qizhi W U Liming SUI Zhitong |
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| Affiliation: | Northeasiern Unirersity.Shenyang 110006 |
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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. |
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| Keywords: | artificial neural network genetic algorithm optimization of composition boron MgO-B_2O_3 SiO_2 slag |
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