A Soft Sensor Modeling Method Based on Self-Adaptive Fuzzy Gauss Kernel Clustering

被引：0

作者：

Xia Y. ^{[1
]}

Yang H. ^{[1
]}

机构：

[1] Key Laboratory of Advanced Control in Light Industry Process of Ministry of Education, Jiangnan University, Wuxi, 214122, Jiangsu

来源：

Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2017年 / 51卷 / 06期

关键词：

Adaption; Fuzzy Gauss kernel clustering; Multi-model; Probability-weighted;

D O I：

10.16183/j.cnki.jsjtu.2017.06.013

中图分类号：

学科分类号：

摘要：

It is difficult for a single model to express the complicated production process, and it often results in low accuracy of prediction and poor performance of generalization. This paper presents a multi-model fusion method based on probability weight and self-adaptive fuzzy Gauss kernel clustering. The method determines cluster centers according to dispersion of the samples in a high dimensional space. The weight of every sub-model is given by Bayesian posterior method. The method can overcome the limitation of single-model forecast and improve traditional multi-model fusion methods for obtaining higher prediction accuracy. © 2017, Shanghai Jiao Tong University Press. All right reserved.

引用

页码：722 / 726

页数：4

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