Abstract

Prof. LotfiAskarZadeh had revolutionized the field of logics by proposing a novel logic, Fuzzy Logic, in 1965 where there is smooth transition between different classes due to overlapping of membership functions, and each element in fuzzy set has a degree of membership. Fuzzy Logic was considered appropriate to represent any vague or ambiguous situation of the real life problems. It also has the provision of allowing linguistic variables whose truth values may vary between 0 and 1; in contrast to two values of classical logic. Quite recently, Neutrosophic Logic was proposed by Florentine Smarandache, which is based on non-standard analysis that was given by Abraham Robinson in 1960s. Neutrosophic Logic was developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision, undefined, unknown, incompleteness, inconsistency, redundancy, and contradiction that encompasses the shortcomings of every other logic studied in the past. All the factors stated are very integral to human thinking, as it is very rare that we tend to conclude/judge in definite environments, imprecision of human systems could be due to the imperfection of knowledge that human receives (observation) from the external world. Imperfection leads to a doubt about the value of a variable, a decision to be taken or a conclusion to be drawn for the actual system. Multiple factors could lead to uncertainty like incomplete knowledge (ignorance of the totality, limited view on a system because of its complexity), stochasticity (the case of intrinsic imperfection where a typical and single value does not exist), or the acquisition errors (intrinsically imperfect observations, the quantitative errors in measures). This talk would focus on the overlapping regions of the fuzzy systems in which a method has been proposed for using neutrosophic logic and assign a triplet of the form (t, i, f) for the points that are spanned by overlapping ranges, in such a way that every such output is assigned a true, indeterminate and false value.

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