Modeling the Performance of an Industrial Process Based on Neural Networks and Data Mining

被引：0

作者：

Aghvami, S. Sara ^{[1
]}

Shandiz, Heider T. ^{[1
,2
]}

Motlagh, M. R. Jahed

机构：

[1] Shahrood Univ Tech, Shahrood, Iran

[2] Iran Univ Sci & Tech, Shahrood, Iran

来源：

MEMS, NANO AND SMART SYSTEMS, PTS 1-6 | 2012年 / 403-408卷

关键词：

PLS; Neural Networks; Data Mining; Modeling; Boiler;

D O I：

10.4028/www.scientific.net/AMR.403-408.3544

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Data Mining has been applied to the world of industrial process. Through this paper, modeling of such a process, a boiler, is discussed focusing on the two methods of Partial Least Square (PLS) Regression and Neural Networks. In modeling the system behavior, the former has the capability of reducing the database dimension and taking to account the latent relations between data, while the later handles the nonlinearity of the process in order to predict the system response through the database of observed boiler operation data.

引用

页码：3544 / +

页数：2

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