Using self-organizing map in a computerized decision support system

被引：0

作者：

Sirola, M ^{[1
]}

Lampi, G ^{[1
]}

Parviainen, J ^{[1
]}

机构：

[1] Helsinki Univ Technol, Lab Comp & Informat Sci, FIN-02015 Helsinki, Finland

来源：

NEURAL INFORMATION PROCESSING | 2004年 / 3316卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Modern computerized decision support systems have developed to their current status during many decades. The variety of methodologies and application areas has increased during this development. In this paper neural method Self-Organizing Map (SOM) is combined with knowledge-based methodologies in a rule-based decision support system prototype. This system, which may be applied for instance in fault diagnosis, is based on an earlier study including compatibility analysis. A Matlab-based tool can be used for example in fault detection and identification. We show with an example how SOM analysis can help decision making in a computerized decision support system. An error state model made in Simulink programming environment is used to produce data for the analysis. Quantisation error between normal data and error data is one significant tool in the analysis. This kind of decision making is necessary for instance in state monitoring in control room of a safety critical process in industry.

引用

页码：136 / 141

页数：6

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