Title :
An intelligent hierarchical decision architecture for operational test and evaluation
Author :
Beers, Major Suzanne M ; Vachtsevanos, George J.
Author_Institution :
Air Force Oper. Test & Evaluation Center, United States Air Force, USA
Abstract :
Decision-makers long for information that will make their decision processes easy and accurate. A methodology is proposed which begins with low information-content data, such as that derived from system testing, and aggregates/synthesizes the information to a higher information-content level, where it is meaningful to the decision-maker. The entire methodology, termed the intelligent hierarchical decision architecture, is composed of four stages which takes low-level test data gathered at the functional performance information level as input and the final output is a probabilistic bound on the system performance at the operational task-accomplishment information level
Keywords :
artificial intelligence; decision theory; equipment evaluation; decision processes; information aggregation; information synthesis; intelligent hierarchical decision architecture; low information-content data; operational evaluation; operational task-accomplishment information level; operational test; Clustering algorithms; Clustering methods; Fuzzy sets; Fuzzy systems; Performance evaluation; System performance; System testing;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.551765