Multi-modeling of pH neutralization processes using improved k-means clustering based on new validity function
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Multi-modeling of pH neutralization processes using improved k-means clustering based on new validity function
CIESC JournalIssue 8, Pages: 2051-2055(2007)
作者机构:
浙江大学信息学院控制系工业控制研究所
作者简介:
基金信息:
DOI:
CLC:
Online First:05 August 2007,
Published:05 August 2007
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ZHOU Lifang, ZHOU Luwen, ZHAO Yuhong. Multi-modeling of pH neutralization processes using improved k-means clustering based on new validity function[J]. CIESC Journal, 2007, (8): 2051-2055.
DOI:
ZHOU Lifang, ZHOU Luwen, ZHAO Yuhong. Multi-modeling of pH neutralization processes using improved k-means clustering based on new validity function[J]. CIESC Journal, 2007, (8): 2051-2055.DOI:
Multi-modeling of pH neutralization processes using improved k-means clustering based on new validity function
The modeling and control of pH neutralization processes is a difficult problem in the field of process control.A multi-modeling method using an improved k-means clustering based on a new validity function is proposed in this paper.There are some common problems
including the number of clusters assumed as a priori knowledge and initial cluster centers selected randomly for classical k-means clustering.The proposed algorithm is used to compute initial cluster centers and a new validity function is added to determine the appropriate number of clusters
then partial least squares (PLS) is used to construct the regression equation for each local cluster.Simulation results showed that multiple models using the proposed algorithm gave good performance
and the feasibility and validity of the proposed algorithm was verified.