郑瑞轩等：炼钢合金减量化智能控制模型及其应用 ·1697 2003.24(4):44) performance prediction of iron ore fines and the ore-blending [16]Lu S,Lu Z.A new clustering algorithm for categorical attributes. programming problem in sintering.Int J Miner Metall Mater, Int J Miner Metall Mater,2000,7(4):318 2014.21(8):741 [17]Geng Z,Liu R.Optimization research on the "deoxidation [23]Vujic S,Benovic T,Miljanovic I,et al.Fuzzy linear model for alloying"batching scheme of molten steel based on linear production optimization of mining systems with multiple entities. programming method /I Materials Science.Energy Technology Int J Miner Metall Mater,2011,18(6):633 And Power Engineering III.Hohhot,019:02007 [24]Xu Z,Mao Z Z.Analysis and prediction of influencing factor on [18]Ammar E S,Eljerbi T.On solving fuzzy rough multiobjective element recovery in ladle furnace./ron Steel,2012,47(3):34 integer linear fractional programming problem.Intell Fuy Syst, (徐枯，毛志忠.钢包精炼炉元素收得率的影响因素分析及预报 2019,37(5):6499 钢铁，2012,47(3)：34) [19]Wang E J,Tsou C S.A simple multiple objective linear [25]Zhang S Y,Bao Y P.Zhang C J,et al.Prediction model of programming model on customization manufacturing for metal aluminum consumption with BP neural networks in IF steel steel making effectiveness /2014 IEEE International Conference production.Chin J Eng,2017,39(4):511 on Industrial Engineering and Engineering Management. (张思源，包燕平，张超杰，等.BP神经网络F钢铝耗的预测模型 Selangor,2014:1285 工程科学学报，2017,39(4)：511) [20]Chen X D,Bao K J,Du B.The application of fuzzy linear [26]Yu P,Zhan D P,Jiang Z H,et al.Development of a terminal programming in LD converter ferroalloy model control system. composition prediction model for steel refing with ladle furnace.J Jiangsu Uniy Sci Technol,2002,23(1):66 Mater Metall,2006,5(1):20 (陈晓东，鲍可进，杜斌.模糊线性规划在转炉合金模型中的应 (于鹏，战东平，姜周华，等.LF精炼终点成分预报模型开发.材 用.江苏大学学报（自然科学版），2002,23(1)：66) 料与治金学报，2006,5(1)：20) [21]Xu J.The Optimal Control of LF Alloying Component Based on [27]Cui K,Jing X.Research on prediction model of geotechnical Fuzy Programming [Dissertation].Shenyang:Northeastern parameters based on BP neural network.Neural Comput Appl, University,2012 2019,31(12):8205 (徐健.基于模糊规划的LF炉合金优化控制[学位论文].沈阳： [28]Liu X.Wen B.Wang X H,et al.Prediction of hot ductility of low- 东北大学，2012) carbon steels based on BP network.Int J Miner Metall Mater, [22]Yan B J,Zhang J L,Guo H W,et al.High-temperature 2001.08(03):1822003, 24（4）：44） Lu S, Lu Z. A new clustering algorithm for categorical attributes. Int J Miner Metall Mater, 2000, 7（4）: 318 [16] Geng Z, Liu R. Optimization research on the “ deoxidation alloying” batching scheme of molten steel based on linear programming method // Materials Science, Energy Technology And Power Engineering III. Hohhot, 2019: 020070 [17] Ammar E S, Eljerbi T. On solving fuzzy rough multiobjective integer linear fractional programming problem. J Intell Fuzzy Syst, 2019, 37（5）: 6499 [18] Wang E J, Tsou C S. A simple multiple objective linear programming model on customization manufacturing for metal steel making effectiveness // 2014 IEEE International Conference on Industrial Engineering and Engineering Management. Selangor, 2014: 1285 [19] Chen X D, Bao K J, Du B. The application of fuzzy linear programming in LD converter ferroalloy model control system. J Jiangsu Univ Sci Technol, 2002, 23（1）: 66 （陈晓东, 鲍可进, 杜斌. 模糊线性规划在转炉合金模型中的应 用. 江苏大学学报(自然科学版), 2002, 23（1）：66） [20] Xu J. The Optimal Control of LF Alloying Component Based on Fuzzy Programming [Dissertation]. Shenyang: Northeastern University, 2012 （ 徐健. 基于模糊规划的LF炉合金优化控制[学位论文]. 沈阳: 东北大学, 2012） [21] [22] Yan B J, Zhang J L, Guo H W, et al. High-temperature performance prediction of iron ore fines and the ore-blending programming problem in sintering. Int J Miner Metall Mater, 2014, 21（8）: 741 Vujic S, Benovic T, Miljanovic I, et al. Fuzzy linear model for production optimization of mining systems with multiple entities. Int J Miner Metall Mater, 2011, 18（6）: 633 [23] Xu Z, Mao Z Z. Analysis and prediction of influencing factor on element recovery in ladle furnace. Iron Steel, 2012, 47（3）: 34 （徐喆, 毛志忠. 钢包精炼炉元素收得率的影响因素分析及预报. 钢铁, 2012, 47（3）：34） [24] Zhang S Y, Bao Y P, Zhang C J, et al. Prediction model of aluminum consumption with BP neural networks in IF steel production. Chin J Eng, 2017, 39（4）: 511 （张思源, 包燕平, 张超杰, 等. BP神经网络IF钢铝耗的预测模型. 工程科学学报, 2017, 39（4）：511） [25] Yu P, Zhan D P, Jiang Z H, et al. Development of a terminal composition prediction model for steel refing with ladle furnace. J Mater Metall, 2006, 5（1）: 20 （于鹏, 战东平, 姜周华, 等. LF精炼终点成分预报模型开发. 材 料与冶金学报, 2006, 5（1）：20） [26] Cui K, Jing X. Research on prediction model of geotechnical parameters based on BP neural network. Neural Comput Appl, 2019, 31（12）: 8205 [27] Liu X, Wen B, Wang X H, et al. Prediction of hot ductility of low￾carbon steels based on BP network. Int J Miner Metall Mater, 2001, 08（03）: 182 [28] 郑瑞轩等： 炼钢合金减量化智能控制模型及其应用 · 1697 ·