In its simplest form it can be thought of a method of assigning a degree of membership of an attribute to a particular set instead of the conventional logic approach which states that an attribute either belongs to a set or does not.
For example consider a reactor with a temperature of 359 degrees C for which we have defined a high reactor temperature as being 360 degrees C.
To the question "Is the reactor temperature high?" conventional logic would provide the answer "no".
Fuzzy logic however is able to inform you that although the reactor temperature is not above the high value it is nearly there.
This is achieved by providing a degree of membership, between 0 and 1, to indicate how close the temperature is to the high value.
A degree of membership of 1 indicates that a value is definately above the high temperature and 0 indicates definately not high.
Thus to the above question fuzzy logic could give the answer 0.
96 to indicate that the temperature is close to the high value (the actual value depends on how "high" is defined)."
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