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Time-varying neuro-fuzzy model using probability density function techniques for 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, L (reprint author), Shanghai Univ, Coll Mechatron Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.
年:2014
期刊名称:JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION影响因子和分区
卷:84
期:6,SI
页码范围:1249-1260
增刊:增刊
学科:数学
收录情况:SCI(E)(WOS:000330705200007)  
所属部门:机电工程与自动化学院
语言:外文
ISSN:0094-9655
被引频次:1
人气指数:48
浏览次数:48
关键词:batch processes; probability density function (PDF) shape of modelling error; time-varying neuro-fuzzy model
摘要:
A time-varying neuro-fuzzy model (TNFM) based on the probability density function (PDF) technique is proposed in this paper. It is able to describe the characteristics of repetition of batch process by using the input-output data information of batch axes and time axes separately. More specifically, the parameters of time-varying neuro-fuzzy are functions of time during one batch, while it can be looked as uniform values from the viewpoint of batch to batch. Moreover, it converts the modelling p ...More
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