DEVELOPMENT AND APPLICATION OF AN EXPERT SYSTEM WITH REAL TIME LEARNING OPERABILITY FOR AUTOMATED INDUSTRIAL AND PORTUARY SYSTEMS

被引：0
|
作者：
De Andrade, Alexandre Acacio [1 ]
Pereira, Sergio Luiz [1 ]
Dias, Eduardo Mario [1 ]
Fontana, Caio Fernando [1 ]
机构：
[1] Univ Sao Paulo, Polytech Sch, GAESI Grp, Elect Power & Automat Engn Dept, BR-05508900 Sao Paulo, Brazil
来源：
COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS | 2008年
关键词：
Leave Machine learning; Industrial Automation; Data Mining; Supervisory and Specialist Systems - Interconnection;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the development and tests of a specialist system based on data mining and that possesses the learning capacity is presented. The referred system was termed as NESISES (Neural System of Integration for Supervisory and Expert Systems). It operates in real time with industrial automation supervisory systems and whose aim is to minimize the frequent knowledge engineering procedures for constantly updating the base of knowledge of an Expert System (ES). NESISES was validated in both the laboratory as well as in an automation application at the Santos seaport, Santos (Brazil).
引用
收藏
页码：150 / 155
页数：6
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