Reasoning with uncertain data 
Here is an expert system user interface example that elicits both
the value of an attribute and the user's confidence in that value:
When the inference engine evaluates a rule with uncertain premise attribute
values the following methods might be considered for
combining two confidence factors (CFs) in the range 0% to 100% and
designated CF1 and CF2:
|Minimum||Use smaller of CF1, CF2|
|Maximum||Use larger of CF1, CF2|
|Average||(CF1 + CF2)/2|
|Probability Sum||CF1 + CF2/100 x (100-CF1)|
|Multiplication||(CF1 x CF2)|
Some examples show how
the choice of method is driven by the circumstances in which CFs
must be combined.
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