Regression using fuzzy adaptive resonant theory neural network

被引：0
|
作者：
Calavia, R. [1 ]
Brezmes, J. [1 ]
Ionescu, R. [1 ]
Llobet, E. [1 ]
机构：
[1] Univ Rovira & Virgili, Dept Elect Engn, Tarragona 43007, Spain
来源：
ELECTRONICS LETTERS | 2006年 / 42卷 / 24期
关键词：
D O I：
10.1049/el:20062764
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A new neural network paradigm based on fuzzy adaptive resonant theory, which yields quantitative results, is presented. The performance of this network in building calibration models for quantitative gas analysis is estimated and compared with other well-established methods. A faster training phase and higher accuracy in regression characterise the new paradigm.
引用
收藏
页码：1415 / 1416
页数：2
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