CALIBRATION OF NONLINEAR ANALYTICAL SYSTEMS BY A NEURO-FUZZY APPROACH

被引：10

作者：

WALCZAK, B ^{[1
]}

WEGSCHEIDER, W ^{[1
]}

机构：

[1] GRAZ UNIV,INST ANALYT CHEM MICRO & RADIOCHEM,A-8010 GRAZ,AUSTRIA

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1994年 / 22卷 / 02期

关键词：

D O I：

10.1016/0169-7439(93)E0077-H

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Building in of fuzzy logic into the neural network structure and application of the back-propagation learning algorithm allows construction of the neuro fuzzy system (NFS). The performance of this approach in calibration of the non-linear systems was evaluated using simulated and experimental data sets. A comparison of the obtained results with an outcome of several other approaches, i.e., neural networks, and principal component analysis-neural networks, was performed.

引用

页码：199 / 207

页数：9

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