FUZZY BI IDEALS OF GAMMA NEAR RING

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Bol I am very pleased to submit this book. In this book contains T -Fuzzy Bi-ideals of Gamma Near-rings, Spherical Fuzzy Bi-ideals of Gamma Near-rings, Spherical Interval-valued Fuzzy Bi-ideals ofGamma Near-rings, Spherical Cubic Bi-ideals of Gamma Near-rings, Double Framed Soft Fuzzy Bi-ideal of GammaNear-rings, Bipolar Fuzzy Bi-ideals of Gamma Near-rings, Conclusion. The concept of fuzziness as described by L.A. Zadeh in 1965 includes imprecision, uncertainty and degree of truthfulness of values. A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership function which assigns to each object a grade of membership ranging between zero and one. A fuzzy set in a universe of discourse X is a function of the form : X ¿ [0, 1]. Membership functions characterize fuzziness (i.e., all the information in fuzzy set), whether the elements in fuzzy sets are discrete or continuous. Membership functions can be defined as a technique to solve practical problems by experience rather than knowledge. Membership functions are represented by graphical forms. Rules for defining fuzziness are fuzzy too.

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I am very pleased to submit this book. In this book contains T -Fuzzy Bi-ideals of Gamma Near-rings, Spherical Fuzzy Bi-ideals of Gamma Near-rings, Spherical Interval-valued Fuzzy Bi-ideals ofGamma Near-rings, Spherical Cubic Bi-ideals of Gamma Near-rings, Double Framed Soft Fuzzy Bi-ideal of GammaNear-rings, Bipolar Fuzzy Bi-ideals of Gamma Near-rings, Conclusion. The concept of fuzziness as described by L.A. Zadeh in 1965 includes imprecision, uncertainty and degree of truthfulness of values. A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership function which assigns to each object a grade of membership ranging between zero and one. A fuzzy set in a universe of discourse X is a function of the form : X ¿ [0, 1]. Membership functions characterize fuzziness (i.e., all the information in fuzzy set), whether the elements in fuzzy sets are discrete or continuous. Membership functions can be defined as a technique to solve practical problems by experience rather than knowledge. Membership functions are represented by graphical forms. Rules for defining fuzziness are fuzzy too.


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