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IJSTR >> Volume 2- Issue 2, February 2013 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Development Of An Adaptive Soft Sensor Based On FCMILSSVR

[Full Text]

 

AUTHOR(S)

Ebrahim Gomnam, Hooshang Jazayeri-rad

 

KEYWORDS

Keywords- soft sensor, incremental least square support vector regression, fuzzy c-means clustering, data mining

 

ABSTRACT

Abstract- Facing with dynamic environment of industrial plants involves us design soft sensors capable of online learning. To response this requirement, an adaptive soft sensor based on a combination of Least Square Support Vector Regression (LSSVR) with Fuzzy C-Means (FCM) clustering is proposed in this paper. In this approach, first the samples are divided into several partitions. Consequently, for each partition we develop a local model using a new formulation of LSSVR which enables incremental learning. The proposed method is implemented on a chemical plant and compared with the online Support Vector Regression (SVR) algorithm. Simulation results indicate that the proposed method improves the generalization ability of soft sensor and the computation time decreases to a large extent in comparison to the online SVR.

 

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