[1]LIU Huan,WANG Jun,DENG Zhaohong,et al.A cascaded hidden space fuzzy C-regression algorithmand its application in multi-model modeling for thefermentation process[J].CAAI Transactions on Intelligent Systems,2016,11(5):670-679.[doi:10.11992/tis.201508015]
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A cascaded hidden space fuzzy C-regression algorithmand its application in multi-model modeling for thefermentation process

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 5 Page number: 670-679 Column: 学术论文—机器学习 Public date: 2016-11-01
Title:
A cascaded hidden space fuzzy C-regression algorithmand its application in multi-model modeling for thefermentation process
Author(s):
LIU Huan;  WANG Jun;  DENG Zhaohong;  WANG Shitong
School of Digital Media, JiangNan University, WuXi 214122, China
Keywords:
hidden space feature mapping; extreme learning machine; principal component analysis; fuzzy C-regression algorithm; multilayer neural network; multi-model modeling.
CLC:
TP181
DOI:
10.11992/tis.201508015
Abstract:
The switching regression algorithm FCR is sensitive to noise data and outliers. The algorithm also has low levels of capability for dealing with complex data. In order to handle these problems, an improved fuzzy C-regression algorithm is proposed based on cascaded hidden space. In our method, principal component analysis is combined with extreme machine learning feature mapping and multilayer feedforward neural networks. The experimental results show that our proposed method is more stable as regards noise data and outliers, and thus more suitable for handling complex data and multi-model modeling problems for the fermentation process.
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