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.