Naslov
An Efficient Automated Learning of Qualitative Process Models

Autori
Bogunović, Nikola ; Jagnjić, Željko ; Jović, Franjo

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
The 4th Asian Control Conference Proceedings / Wang, Qing G. - Singapur : Causal Productions, 2002, 2107-2111

Skup
The 4th Asian Control Conference

Mjesto i datum
Singapur, 25.09.2002. - 27.09.2002

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Process modeling; Qualitative modeling; Process identification

Sažetak
Process control system design relies in the main part on the suitable modeling and simulation of the underpinning operation of the physical system. The paper presupposes that the qualitative dependency among process variables is the fundamental model that must be generated from quantitative across time observations. Hence, a novel approach to qualitative interpretation of sensory data taken over time from the industrial plant is presented. Contrary to the most current techniques that derive a single qualitative differential equation, the described approach extracts diverse qualitative expressions (correlative knowledge) from the set of observed process variables from many distinctive and interesting time intervals. The technique is based on mapping quantitative time series data to binary coded qualitative difference vectors of process variables that significantly accelerates the modeling process. An experimental evaluation of the technique is shown.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA