Question

What is meant by fuzzy logic what is fuzzification and defuzzification?

Answer 1

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Fuzzification and Defuzzification are commonly used terms in Fuzzy Logic as a part of Artificial Intelligence. 

Fuzzification can be thought of as representing any real world feeling or quantity such as warm, happy, love, hungry and so on, into a mathematical model. For example, let's consider "beautiful" to be fuzzified. 

Let's quantify it into a mathematical model. The question to be asked is "how much beautiful?". Beauty can be classified into Very beautiful (Pretty), Average (Good Looking), Not at all beautiful (Ugly or ordinary). Now let's give them mathematical values...1.0 - 0.7 can be thought of as very beautiful, 0.7 - 0.4 can be thought of as average and 0.4 - 0.0 can be thought of as ordinary, where 1.0 is regarded as more beautiful than 0.8. Based on this , we can classify an object into ranges or values based on its appearance. 

This is what fuzzification is. Defuzzification is the inverse, where fuzzy values are converted back to a crisp value after operator application and truncation.