Local modelling with radial basis function networks (vol 50, pg 179, 2000)

被引：0

作者：

Walczak, B ^{[1
]}

Massart, DL ^{[1
]}

机构：

[1] Free Univ Brussels, ChemoAC, B-1090 Brussels, Belgium

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2000年 / 51卷 / 02期

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Different types of radial basis function networks (RBFN) training algorithms are described and compared. Advantages and drawbacks of some of these algorithms are demonstrated on simulated and real data. Interpretability of the final models is emphasized. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：217 / +

页数：21

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