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What is Approximation

Handbook of Research on Advances and Applications of Fuzzy Sets and Logic
The nearest value for representing the result in some situations.
Published in Chapter:
Rough Neutrosophic Multisets: Operations Over Rough Neutrosophic Multisets
Suriana Alias (Universiti Teknologi MARA, Malaysia), Daud Mohamad (Universiti Teknologi MARA, Malaysia), and Adibah Shuib (Universiti Teknologi MARA, Malaysia)
DOI: 10.4018/978-1-7998-7979-4.ch025
Abstract
The effect of uncertainty in information raises human logical thinking due to many variabilities from expert decision making. The generalization of rough neutrosophic multisets theory tries to overcome this problem. The rough neutrosophic multisets allow the multiplicity of information represented by truth membership sequences, indeterminacy membership sequences, and falsity membership sequences. The lower and upper approximations belong to this triple membership sequence, making the information result more valuable since the relationship among this membership sequence makes sense. This chapter introduces the generalization of rough neutrosophic multisets with some operators and an illustrative example. The rough neutrosophic multisets basic operators, algebraic operators, and “AND” and “OR” operators are defined with some property propositions.
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Voice-Based Speaker Identification and Verification
It is the process where any data is intentionally similar but not exactly equal to something else.
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Transforming Lesson Design through Animation: Preservice Mathematics Teachers' Plan-Imations
A means of practicing or providing a substitute or representation that closely imitates an intended outcome, but which may have a different pace, focus, or intent.
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