[1]张孙力,杨慧中.基于改进混合蛙跳算法的软测量建模方法[J].南京理工大学学报(自然科学版),2017,41(02):173.[doi:10.14177/j.cnki.32-1397n.2017.41.02.006]
 Zhang Sunli,Yang Huizhong.New soft-sensor modeling method based on improved shuffledfrog leaping algorithm[J].Journal of Nanjing University of Science and Technology,2017,41(02):173.[doi:10.14177/j.cnki.32-1397n.2017.41.02.006]
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基于改进混合蛙跳算法的软测量建模方法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年02期
页码:
173
栏目:
出版日期:
2017-04-30

文章信息/Info

Title:
New soft-sensor modeling method based on improved shuffledfrog leaping algorithm
文章编号:
1005-9830(2017)02-0173-08
作者:
张孙力杨慧中
江南大学 教育部轻工过程先进控制重点实验室,江苏 无锡 214122
Author(s):
Zhang SunliYang Huizhong
Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),Jiangnan University,Wuxi 214122,China
关键词:
混合蛙跳算法 动态权值 高斯变异算子 聚类中心
Keywords:
shuffled frog leaping algorithm dynamic weight Gaussian mutation operators clustering centers
分类号:
TP274
DOI:
10.14177/j.cnki.32-1397n.2017.41.02.006
摘要:
针对混合蛙跳算法的寻优机制在寻优过程中易陷入局部最优和收敛效果不理想的问题,该文提出一种改进的混合蛙跳算法。该算法在更新群中最差个体时同步更新最优个体。更新最差个体步长时引入上一次的移动步长并赋予动态权值。改进算法舍弃了原算法中用随机值代替最差值的做法,引入高斯变异算子对最差个体进行高斯变异,使种群进化更趋合理。将改进的混合蛙跳算法运用到模糊C均值聚类算法的聚类中心优化中,得到最优的聚类中心。利用该聚类中心对样本进行模糊C均值聚类,并用高斯过程回归对各类样本子集分别建立对应的子模型,通过加权得到系统输出。以双酚A生产过程结晶单元为例进行仿真,对装置出口处的苯酚浓度进行软测量建模,获得了较好的实验结果。
Abstract:
In order to solve the problem that the optimization mechanism of the shuffled frog leaping adgorithm(SFLA)is easily falling into the local optimum during the optimization process and the convergence result is unsatisfactory,an improved shuffled frog leaping algorithm(ISFLA)is proposed here.The worst individual and the best individual among subgroups are updated simultaneously.The last moving step-length with the dynamic weight is applied to update the worst individual step-length and makes the population evolution more rational after the Gaussian mutation operator is used on the worst individual instead of the original random mutation operator.The optimal clustering result is calculated with the application of the ISFLA in the optimization of clustering centers by using the fuzzy C-means clustering algorithm.The clustering centers are optimized by the fuzzy C-means clustering algorithm.In addition,the final result is outputted by weighted Gaussian sub-models towards different categories.A sample of the crystallization unit of a bisphenol-A production is applied to make a simulation,and the soft-sensor model of the phenol concentration is built at the exit device with a good experiment result.

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相似文献/References:

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 YU Hua,HUANG Cheng-wei,ZHANG Xiao-dan,et al.Shuffled Frog-leaping Algorithm Based Neural Network and Its Application in Speech Emotion Recognition[J].Journal of Nanjing University of Science and Technology,2011,(02):659.
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备注/Memo

备注/Memo:
收稿日期:2016-06-21 修回日期:2016-09-04
基金项目:国家自然科学基金(61273070); 中央高校基本科研业务费专项资金资助(JUSRP51733B)
作者简介:张孙力(1992-),男,硕士生,主要研究方向:软测量建模,E-mail:zhangsunli@163.com; 通讯作者:杨慧中(1955-),女,博士,教授,主要研究方向:复杂过程建模和优化控制,E-mail:yhz_jn@163.com。
引文格式:张孙力,杨慧中.基于改进混合蛙跳算法的软测量建模方法[J].南京理工大学学报,2017,41(2):173-180.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-04-30