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The probability density function based neuro-fuzzy model and its application in batch processes
文献类型:期刊论文
作者:Jia, Li[1]  Yuan, Kai[2]  
机构:[1]Shanghai Univ, Coll Mechatron Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.;
[2]Shanghai Univ, Coll Mechatron Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.;
通讯作者:Jia, Li
年:2015
期刊名称:NEUROCOMPUTING影响因子和分区
卷:148
页码范围:216-221
增刊:正刊
收录情况:SCI(E)(WOS:000343840000029)  EI(20143600019219)  
所属部门:机电工程与自动化学院
语言:外文
ISSN:0925-2312
被引频次:2
人气指数:41
浏览次数:41
基金:National Natural Science Foundation of China [61374044]; Shanghai Science Technology Commission [12510709400]; Shanghai Municipal Education Commission [14ZZ088]; Shanghai talent development plan
关键词:Batch process; Probability density function; Neuro-fuzzy model; Modeling error
摘要:
Motivated by the concept of probability density function (PDF) control, a new probability density function (PDF) based neuro-fuzzy model for batch processes is proposed in this paper. The probability density function (PDF) of modeling error is introduced as a criterion to measure the performance of the neuro-fuzzy model of batch processes. More specifically, the neuro-fuzzy model parameter updating approach is transformed into the shape control of the probability density function (PDF) of the mo ...More
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