Title :
Critical observations in a diagnostic problem
Author :
Christopher, Cody James ; Cordier, Marie-Odile ; Grastien, Alban
Author_Institution :
Artificial Intell. Group, Australian Nat. Univ., Canberra, ACT, Australia
Abstract :
We claim that presenting a human operator in charge of repairing a faulty system with a small subset of observations relevant to the failure improves awareness and confidence of the operator. Consequently, we introduce the problem of finding a set of relevant observations (called the critical observations) that can be used to derive the same diagnosis as the full problem. We show how this problem can be solved and illustrate its benefits on a real diagnostic problem.
Keywords :
power engineering computing; power system faults; critical observation; diagnostic problem; faulty system; Computational modeling; Conferences; Context; Electricity; Government; Sensor systems;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7039411