fuzzy logic

Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1. By contrast, in Boolean logic, the truth values of variables may only be 0 or 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false.
The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by Lotfi A. Zadeh. Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.

Fuzzy Logic Algorithm:
1. Define the linguistic variables and terms (initialization)
2. Construct the membership functions (initialization)
3. Construct the rule base (initialization)
4. Convert crisp input data to fuzzy values using the membership functions (fuzzification)
5. Evaluate the rules in the rule base (inference)
6. Combine the results of each rule (inference)
7. Convert the output data to non-fuzzy values (defuzzification)
Why fuzzy logic:
• Ease of understand: mathmatical concepts that fuzzy logic depend on is simple.
• Flexibility: in any fuzzy system, set of additional functions can added without needed to rebuild of system newly.
• Appility to deal with imprecise data efficiently: in real world, every thing appears imprecise even check it carefully, fuzzy logic is characterized by its ability to deal with the lack of precision and get very good results using inaccurate data
• Fuzzy logic depend on natural language