Title :
A hybrid intelligent system for process operations support
Author :
Xia, Qijun ; Rao, Ming
Author_Institution :
Dept. of Chem. & Mater. Eng., Alberta Univ., Edmonton, Alta., Canada
Abstract :
Presents an intelligent operation support system (IOSS) using rich knowledge representation and hybrid reasoning strategy. The functional requirements and desired features for IOSS are defined. The human operator´s recognition behavior is analyzed. It is shown that a hybrid reasoning environment that combines case-based reasoning (CBR), model-based reasoning (MBR) and rule-based reasoning (RBR) is consistent with operator´s problem solving. A multidimensional problem solving model is proposed to incorporate these requirements and human recognition behavior. IOSS is designed by using the problem solving model as the guide. The implementation of IOSS in a pulp production process is presented
Keywords :
case-based reasoning; decision support systems; distributed control; knowledge based systems; knowledge representation; model-based reasoning; paper industry; problem solving; process control; case-based reasoning; functional requirements; human operator´s recognition behavior; human recognition behavior; hybrid intelligent system; hybrid reasoning strategy; intelligent operation support system; model-based reasoning; multidimensional problem solving model; operator´s problem solving; process operations support; pulp production process; rich knowledge representation; rule-based reasoning; Artificial intelligence; Control systems; Distributed control; Humans; Hybrid intelligent systems; Industrial control; Information management; Management information systems; Problem-solving; Production systems;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.635174
