An expert system that has rules of the form If w is low and x is high then y is intermediate, where w
and x are input variables and y is the output variable, is called a:
A.
Fuzzy expert system
B.
Realistic expert system
C.
Neural network
D.
Boolean expert system
Explanation:
A fuzzy expert system is an expert system that uses fuzzy membership functions and rules, instead of
Boolean logic, to reason about data. Thus, fuzzy variables can have an approximate range of values
instead of the binary True or False used in conventional expert systems. When it is desired to
convert the fuzzy output to a single value, defuzzification is used. One approach to defuzzification is
the CENTROID method. With this method, a value of the output variable is computed by finding the
variable value of the center of gravity of the membership function for the fuzzy output value.
Answers Neural network and Realistic expert system are distracters, and answer Boolean expert
system is incorrect since it refers to Boolean values of one or zero.