The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 89-663
Full Name: Eduardo Mario Dias
Position: Professor
Age: ON
Sex: Male
Address: Av. Prof. Luciano Gualberto, travessa 3, nº 158, Cep. 05507-010 – Cidade Universitária, São Paulo/SP
Country: BRAZIL
Tel: 3091 5113
Tel prefix: +55 11
Fax:
E-mail address: emdias@pea.usp.br
Other E-mails: wellington.usp@gmail.com
Title of the Paper: Using data mining techniques for development expert systems equipped with learning capabilities for use in automated industrial plants
Authors as they appear in the Paper: Alexandre Acácio de Andrade, Sergio Luiz Pereira, Eduardo Mario Dias, Caio Fernando Fontana
Email addresses of all the authors: alacacio@terra.com.br, sergio@pea.usp.br, emdias@pea.usp.br, caio.fontana@poli.usp.br
Number of paper pages: 10
Abstract: The use of expert systems gained importance with the growing amount of data that the current plants generate automated, 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 plant.
Keywords: Data mining, Machine learning, Industrial automation, Supervisory and specialist systems - Interconnection
EXTENSION of the file: .pdf
Special (Invited) Session: Devolopment and Application of na Expert System with Real Time Learning Operability for Automated Industrial and Portuary Systems
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