Neuro-fuzzy modelling of power plant flue-gas emissions

被引：29
|
作者：
Ikonen, E
Najim, K
Kortela, U
机构：
[1] Univ Oulu, Infotech Oulu, Oulu 90014, Finland
[2] Dept Proc Engn, Syst Engn Lab, Oulu 90014, Finland
[3] Ecole Natl Super Ingn Genie Chim, Proc Control Lab, F-31078 Toulouse, France
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2000年 / 13卷 / 06期
基金：
芬兰科学院;
关键词：
fluidised-bed; fuzzy systems; neural nets; process models; thermal plants;
D O I：
10.1016/S0952-1976(00)00054-3
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper concerns process modelling using fuzzy neural networks. In distributed logic processors (DLP) the rule base is parameterised. The DLP derivatives required by gradient-based training methods are given, and the recursive prediction error method is used to adjust the model parameters. The power of the approach is illustrated with a modelling example where NO, emission data from a full-scale fluidised-bed combustion district heating plant are used. The method presented in this paper is general, and can be applied to other complex processes as well. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：705 / 717
页数：13
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