周颖等：BCOISOA-BP网络在磨矿粒度软测量中的应用 ·1551· rameters in the RBF Neural Netcorks Dissertation ]Shanghai: frequency-based PID controller using seeker optimization algo- East China University of Science and Technology,2014 rithm//2016 6th Conference on Thermal Pouer Plants (CTPP). (周维华.RBF神经网络隐层结构与参数优化研究[学位论 Tehran,2016:52 文].上海：华东理工大学，2014) [11]Yu S W,Ding JM,Cao ZQ.Improved seeker optimization algo- [5]Wang T.Research on Predictive Control Method based on GAPSO rithm application in weld image segmentation.J Railay Sci Algorithm and RBF Neural Netork Dissertation].Taiyuan: Eng,2015,12(6):1471 Taiyuan University of Technology,2015 (余胜威，丁建明，曹中清.改进S0A算法在焊缝图像分割 (王婷.基于GAPSO算法和RBF神经网络预测控制方法的研 中的应用.铁道科学与工程学报，2015,12(6)：1471) 究[学位论文].太原：太原理工大学，2015) [12]Zhou Y,Zhao H M,Chen Y,et al.Soft sensor of particle size of [6]Wang Q.Research on Soft Sensing of Overflone Particle Size for grinding process and based on improved CSAPSO neural net- Grinding Process [Dissertation].Shenyang:Northeastern Univer- works..J Syst Sim,2016,12(28):2946 sity,2009 (周颖，赵慧敏，陈阳，等.基于改进混沌自适应粒子群神经 (王清.磨矿过程溢流粒度软测量研究[学位论文】.沈阳：东 网络的磨矿粒度软测量.系统仿真学报，2016,12(28)： 北大学，2009) 2946) [7]Maji K B,Sree US,Kar R,et al.Butterworth filter design using [13] Zhang Y,Dai Y F,Chen L L,et al.Soft-measuring model for seeker optimization algorithm//2015 International Conference on grinding size based on the improved FOA-ISSVM model.Minin- Science and Technology TICST).PathumThani,2015:298 gR&D,2015,35(11):97 [8]Wei L B,Zhao F.Wang S H.Short-term power load forecasting (张燕，代亚菲，陈玲玲，等.基于改进的OA-LSSVM磨矿 of support vector machine based on parameters optimization of pop- 粒度软测量模型.矿业研究与开发，2015,35(11)：97) ulation search algorithm.Electr Measur Instrum,2016,53(8): [14]Dai W,Chai T Y.Data-driven optimal operational control of complex grinding processes.Acta Autom Sin,2014,40 (9): (魏立兵，赵峰，王思华.基于人群搜索算法优化参数的支持 2005 向量机短期电力负荷预测.电测与仪表，2016,53(8)：45) (代伟，柴天佑.数据驱动的复杂磨矿过程运行优化控制方 [9]Li PZ.The research and application of PM2.5 concentration pre- 法.自动化学报，2014,40(9)：2005) diction model.World Surr Res,2016(2):19 [15]Li Y.Research on the Parameters'Sof Sensing and Synthetic Op- (李培志.P2.5浓度预测模型的研究与应用一基于人群搜 timizing Control of Grinding Process Dissertation ]Dalian 索算法优化后支持向量机模型.调研世界，2016(2)：19) Dalian University of Technology,2006 [10]Parvaneh H,Dizgah S M,Sedighizadeh M,et al.Load frequen- (李勇.磨矿过程参数软测量与综合优化控制的研究[学位 cy control of a multi-area power system by optimum designing of 论文].大连：大连理工大学，2006)周 颖等: BCOISOA鄄鄄BP 网络在磨矿粒度软测量中的应用 rameters in the RBF Neural Networks [ Dissertation]. Shanghai: East China University of Science and Technology, 2014 (周维华. RBF 神经网络隐层结构与参数优化研究[ 学位论 文]. 上海:华东理工大学,2014) [5] Wang T. Research on Predictive Control Method based on GAPSO Algorithm and RBF Neural Network [ Dissertation ]. Taiyuan: Taiyuan University of Technology, 2015 (王婷. 基于 GAPSO 算法和 RBF 神经网络预测控制方法的研 究[学位论文]. 太原:太原理工大学,2015) [6] Wang Q. Research on Soft Sensing of Overflow Particle Size for Grinding Process [Dissertation]. Shenyang: Northeastern Univer鄄 sity, 2009 (王清. 磨矿过程溢流粒度软测量研究[学位论文]. 沈阳:东 北大学,2009) [7] Maji K B, Sree U S, Kar R, et al. Butterworth filter design using seeker optimization algorithm/ / 2015 International Conference on Science and Technology (TICST). PathumThani, 2015: 298 [8] Wei L B, Zhao F, Wang S H. Short鄄term power load forecasting of support vector machine based on parameters optimization of pop鄄 ulation search algorithm. Electr Measur Instrum, 2016, 53 (8 ): 45 (魏立兵, 赵峰, 王思华. 基于人群搜索算法优化参数的支持 向量机短期电力负荷预测. 电测与仪表, 2016,53(8): 45) [9] Li P Z. The research and application of PM2. 5 concentration pre鄄 diction model. World Surv Res, 2016(2): 19 (李培志. PM2. 5 浓度预测模型的研究与应用———基于人群搜 索算法优化后支持向量机模型. 调研世界, 2016(2): 19) [10] Parvaneh H, Dizgah S M, Sedighizadeh M, et al. Load frequen鄄 cy control of a multi鄄area power system by optimum designing of frequency鄄based PID controller using seeker optimization algo鄄 rithm/ / 2016 6th Conference on Thermal Power Plants (CTPP). Tehran, 2016: 52 [11] Yu S W, Ding J M, Cao Z Q. Improved seeker optimization algo鄄 rithm application in weld image segmentation. J Railway Sci Eng, 2015, 12(6): 1471 (余胜威, 丁建明, 曹中清. 改进 SOA 算法在焊缝图像分割 中的应用. 铁道科学与工程学报, 2015, 12(6): 1471) [12] Zhou Y, Zhao H M, Chen Y, et al. Soft sensor of particle size of grinding process and based on improved CSAPSO neural net鄄 works. J Syst Sim, 2016,12(28):2946 (周颖, 赵慧敏, 陈阳, 等. 基于改进混沌自适应粒子群神经 网络的磨矿粒度软测量. 系统仿真学报, 2016,12 ( 28 ): 2946) [13] Zhang Y, Dai Y F, Chen L L, et al. Soft鄄measuring model for grinding size based on the improved FOA鄄鄄LSSVM model. Minin鄄 gR&D, 2015, 35(11): 97 (张燕, 代亚菲, 陈玲玲, 等. 基于改进的 FOA鄄鄄LSSVM 磨矿 粒度软测量模型. 矿业研究与开发, 2015, 35(11): 97) [14] Dai W, Chai T Y. Data鄄driven optimal operational control of complex grinding processes. Acta Autom Sin, 2014, 40 ( 9 ): 2005 (代伟, 柴天佑. 数据驱动的复杂磨矿过程运行优化控制方 法. 自动化学报, 2014, 40(9): 2005) [15] Li Y. Research on the Parameters蒺 Soft Sensing and Synthetic Op鄄 timizing Control of Grinding Process [ Dissertation ]. Dalian: Dalian University of Technology, 2006 (李勇. 磨矿过程参数软测量与综合优化控制的研究[学位 论文]. 大连:大连理工大学,2006) ·1551·