Integrating General Expert Knowledge and Specific Experimental Knowledge in WWTP

Authors

Miquel Sànchez-Marrè miquel@lsi.upc.es
Ulises Cortés ia@lsi.upc.es

Departament de Llenguatges i Sistemes Informàtics
Universitat Politècnica de Catalunya
Edifici C5-Campus Nord
C/ Jordi Girona 1-3
08034 Barcelona, Catalonia, Spain

Manel Poch eqampe@fc.udg.es
Ignasi R-Roda eqamirr@fc.udg.es

Laboratori d'Enginyeria Química i Ambiental.
Facultat de Ciències
Universitat de Girona
Campus de Montilivi
17071 Girona, Catalonia, Spain

Abstract

The development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from past experience (specific experimental knowledge) and to acquire the domain knowledge (general expert knowledge) are the key problems in real-time control AI systems design. These problems increase when the process belongs to an ill-structured domain and it is composed by several complex operational units. Therefore, an integrated AI methodology which combines both kind of knowledge is proposed. This multi- paradigm reasoning provides the target system a wastewater treatment plant (WWTP) with some advantages over other approaches applied to real world systems.

Keywords: Classification. Concept Formation. Knowledge-Based Systems. Wastewater treatment. Environmental Engineering.

Citation:

M. SÓnchez, U. CortÚs, I. R-Roda, M. Poch "Integrating General Expert Knowledge and Specific Experimental Knwoledge in WWPT". IJCAI-95, workshop on Artificial Intelligence and the Environment. pp 75-81. Montreal. Canada

Postscript

You may want a postcript version of the article: Integrating General Expert Knowledge and Specific Experimental Knowledge in WWTP


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