郭东伟等：基于稀疏化鲁棒LS-SVR与多目标优化的铁水硅含量软测量建模 ·1241· Sources,2011,196(14):5873 Neural Netorks,2015,61:85 [11]Li C P.Zheng Y X,Zhang J.Ore grade interpolation model [14]Li C H,Wang Y F,Cai M F,et al.Slope deformation model of based on support vector machines optimized by genetic algo- metal mines transferred underground mining from open-pit based rithms.J Univ Sci Technol Beijing,2013,35(7):837 on support vector machines.J Unie Sci Technol Beijing,2009, (李翠平，郑瑶瑕，张佳.基于遗传算法优化的支持向量机 31(8):945 品位插值模型.北京科技大学学报，2013,35(7)：837) (李长洪，王云飞，蔡美峰，等.基于支持向量机的露天转地 [12]Han Y Y,Gong D W,Sun X Y,et al.An improved NSGA-II 下开采边坡变形模型.北京科技大学学报，2009,31(8)： algorithm for multiobjective lot-streaming flow shop scheduling 945) problem.Int J Prod Res,2014,52(8):2211 [5]Agrama FA.Multi-objective genetic optimization for scheduling [13]Schmidhuber J.Deep learning in neural networks:an overview. a multi-storey building.Autom Constr,2014,44:119郭东伟等: 基于稀疏化鲁棒 LS--SVＲ 与多目标优化的铁水硅含量软测量建模 Sources，2011，196( 14) : 5873 ［11］ Li C P，Zheng Y X，Zhang J． Ore grade interpolation model based on support vector machines optimized by genetic algo￾rithms． J Univ Sci Technol Beijing，2013，35( 7) : 837 ( 李翠平，郑瑶瑕，张佳． 基于遗传算法优化的支持向量机 品位插值模型． 北京科技大学学报，2013，35( 7) : 837) ［12］ Han Y Y，Gong D W，Sun X Y，et al． An improved NSGA--II algorithm for multi-objective lot-streaming flow shop scheduling problem． Int J Prod Ｒes，2014，52( 8) : 2211 ［13］ Schmidhuber J． Deep learning in neural networks: an overview． Neural Networks，2015，61: 85 ［14］ Li C H，Wang Y F，Cai M F，et al． Slope deformation model of metal mines transferred underground mining from open-pit based on support vector machines． J Univ Sci Technol Beijing，2009， 31( 8) : 945 ( 李长洪，王云飞，蔡美峰，等． 基于支持向量机的露天转地 下开采边坡变形模型． 北京科技大学学报，2009，31 ( 8) : 945) ［15］ Agrama F A． Multi-objective genetic optimization for scheduling a multi-storey building． Autom Constr，2014，44: 119 ·1241·