Knowledge representation and reasoning in the presence of uncertainty in an expert system for laboratory reactor selection

1992 ◽  
Vol 31 (1) ◽  
pp. 228-238 ◽  
Author(s):  
Peter J. Hanratty ◽  
Babu Joseph ◽  
Milorad P. Dudukovic
2013 ◽  
Vol 291-294 ◽  
pp. 2557-2561
Author(s):  
Tao Sun ◽  
Hai Bo Liu

The transformer fault diagnosis expert system design knowledge representation and reasoning mechanisms are the key issue. Characteristics of transformer fault diagnosis system based on human experts, learning on the basis of the human expert diagnosis of transformer faults, to build a transformer fault diagnosis expert system of systems architecture, knowledge representation and reasoning mechanisms for a more detailed analysis and discussion.


Robotica ◽  
2001 ◽  
Vol 19 (6) ◽  
pp. 669-674 ◽  
Author(s):  
Jie Yang ◽  
Chenzhou Ye ◽  
Xiaoli Zhang

Traditional expert systems for fault diagnosis have a bottleneck in knowledge acquisition, and have limitations in knowledge representation and reasoning. A new expert system shell for fault diagnosis is presented in this paper to develop multiple knowledge models (object model, rules, neural network, case-base and diagnose models) hierarchically based on multiple knowledge. The structure of the expert system shell and the knowledge representation of multiple models are described. Diagnostic algorithms are presented for automatic modeling and hierarchical reasoning. It will be shown that the expert system shell is very effective in building diagnostic expert systems.


2014 ◽  
Author(s):  
David Braines ◽  
Geeth de Mel ◽  
Chris Gwilliams ◽  
Christos Parizas ◽  
Diego Pizzocaro ◽  
...  

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