南京理工大学学报（自然科学版）2017，Vol.41Issue(2)：173-180,8.DOI:10.14177/j.cnki.32-1397n.2017.41.02.006
基于改进混合蛙跳算法的软测量建模方法
New soft-sensor modeling method based on improved shuffledfrog leaping algorithm
摘要
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.关键词
混合蛙跳算法/动态权值/高斯变异算子/聚类中心Key words
shuffled frog leaping algorithm/dynamic weight/Gaussian mutation operators/clustering centers分类
信息技术与安全科学引用本文复制引用
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(2):173-180,8.基金项目
国家自然科学基金(61273070) （61273070）
中央高校基本科研业务费专项资金资助(JUSRP51733B) （JUSRP51733B）
