A Study on the Effectiveness of Contradiction Values inUpside-Down Logic and De-Plithogenication within PlithogenicSets

Autores/as

  • Takaaki Fujita Independent Researcher, Tokyo, Japan Autor/a
  • Arif Mehmood Department of Mathematics, Institute of Numerical Sciences, Gomal University, Dera Ismail Khan 29050, KPK, Pakistan Autor/a

Palabras clave:

Upside-down-logic, Plithogenic Set, Plithogenic Fuzzy Set, Plithogenic Intuitionistic Fuzzy Set, Plithogenic Neutrosophic Set, Plithogenic Fuzzy Graph

Resumen

n the real world, many reversal phenomena occur, such as cases where a statement once regarded
as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phe-
nomena as a logical system. It inverts the truth and falsity of propositions through contextual transformations,
thereby capturing ambiguity and reversals within reasoning processes.
A Plithogenic Set models elements by means of attribute-based membership and contradiction functions,
extending the classical frameworks of fuzzy, intuitionistic, and neutrosophic sets. However, the role and ef-
fectiveness of Upside-Down Logic within Plithogenic Fuzzy Sets, Plithogenic Intuitionistic Fuzzy Sets, and
Plithogenic Neutrosophic Sets have not yet been sufficiently explored.
To address this gap, this paper investigates Upside-Down Logic in these three plithogenic settings. In partic-
ular, we analyze how contradiction values guide the application of Upside-Down Logic and provide illustrative
examples of its use. Furthermore, we consider application cases of Upside-Down Logic in Plithogenic Fuzzy
Graphs. Through these studies, we aim to demonstrate that Upside-Down Logic offers a formal means to model
reversal phenomena arising from contradictions under uncertainty. We also define a method of resolving con-
tradictions, referred to as De-Plithogenication. Through this process, for instance, a Plithogenic Fuzzy Set can
be transformed into a structure resembling a classical Fuzzy Set.

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Publicado

2025-09-20

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Cómo citar

A Study on the Effectiveness of Contradiction Values inUpside-Down Logic and De-Plithogenication within PlithogenicSets. (2025). Neutrosophic Computing and Machine Learning, 40, 28-65. https://fs.unm.edu/NCML_2/index.php/NCML/article/view/64

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