APPLICATION OF FEEDFORWARD NEURAL NETWORKS AND PARTIAL LEAST-SQUARES REGRESSION FOR MODELING KAPPA-NUMBER IN A CONTINUOUS KAMYR DIGESTER

被引：0

作者：

DAYAL, BS ^{[1
]}

MACGREGOR, JF ^{[1
]}

TAYLOR, PA ^{[1
]}

KILDAW, R ^{[1
]}

MARCIKIC, S ^{[1
]}

机构：

[1] PROCTER & GAMBLE CO,WINTON HILL TECH CTR,CINCINNATI,OH 45224

来源：

PULP & PAPER-CANADA | 1994年 / 95卷 / 01期

关键词：

ARTIFICIAL INTELLIGENCE; MODELS; KAPPA NUMBER; CONTINUOUS DIGESTERS; VERTICAL DESIGN;

D O I：

暂无

中图分类号：

TB3 [工程材料学]; TS [轻工业、手工业、生活服务业];

学科分类号：

0805 ; 080502 ; 0822 ;

摘要：

In this paper we investigate the use of neural networks and the partial least squares regression method to build empirical models for Kappa number using historical data from an industrial, continuous Kamyr digester. The basic ideas behind the two approaches will he presented and their advantages and disadvantages discussed. The predictive abilities of the resulting models and their limitations are evaluated using additional data from the digester and compared to other modelling approaches.

引用

页码：26 / 32

页数：7

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