A hybrid intelligent system for process operations support

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.

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