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This paper deals with Fuzzy logic an idea which is easy to understand. Fuzzy logic provides an alternative way to represent linguistic and subjective attributes of the real world in computing. The cause for selection of fuzzy logic model in this revision is that the system uses fuzzy logic model enables to provide useful results depending on uncertain verbal knowledge just like logic of human being. The value of fuzzy logic model usage here is to reach a general solution by doing only incomplete experiments. It takes long time to use the other methods for such problem. The fuzzy logic provides the quickest way out to the problem prevents to lose. It is a outline of multiple-valued logic which has other than two truth values. It uses the concept of level of membership. In Boolean logic, the truth standards may be only 0 or 1, but in fuzzy logic, they will be any real number between 0 and 1 i.e. the truth values will vary between true and false. Fuzzification which comprises of the development of transforming hard values into grades of membership for linguistic terms of fuzzy sets and Fuzzy set is a set that allows its members to have various degrees of membership within 0 and 1 i.e. within true and false. Fuzzy system is based on a logical system which is much closer to human thinking and natural language.

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