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Neutrosophic set is a part of neutrosophy which studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. Neutrosophic set is a powerful general formal framework that has been…

General Mathematics · Mathematics 2007-05-23 Haibin Wang , Praveen Madiraju , Yanqing Zhang , Rajshekhar Sunderraman

To deal with uncertainty in reasoning, interval-valued logic has been developed. But uniform intervals cannot capture the difference in degrees of belief for different values in the interval. To salvage the problem triangular and…

Artificial Intelligence · Computer Science 2020-01-08 Sandip Paul , Kumar Sankar Ray , Diganta Saha

We propose a new definition of the representation theorem for many-valued logics, with modal operators as well, and define the stronger relationship between algebraic models of a given logic and relational structures used to define the…

Logic in Computer Science · Computer Science 2011-03-02 Zoran Majkic

Maji\cite{maj-13}, firstly proposed neutrosophic soft sets can handle the indeterminate information and inconsistent information which exists commonly in belief systems. In this paper, we have firstly redefined complement, union and…

General Mathematics · Mathematics 2015-02-24 Irfan Deli , Said Broumi

This book presents the advancements and applications of neutrosophics. Chapter 1 first introduces the interval neutrosophic sets which is an instance of neutrosophic sets. In this chapter, the definition of interval neutrosophic sets and…

Logic in Computer Science · Computer Science 2007-05-23 Haibin Wang , Florentin Smarandache , Yan-Qing Zhang , Rajshekhar Sunderraman

Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with…

Artificial Intelligence · Computer Science 2016-11-17 Haibin Wang , Andre Rogatko , Florentin Smarandache , Rajshekhar Sunderraman

Smarandache (2003) introduced a new set-valued fuzzy logic called (nonstandard) neutrosophic logic by using Robinson's nonstandard analysis. However, its definition involved many errors including the illegal use of nonstandard analysis. In…

General Mathematics · Mathematics 2022-08-19 Takuma Imamura

Neutrosophic Analysis is a generalization of Set Analysis, which in its turn is a generalization of Interval Analysis. Neutrosophic Precalculus is referred to indeterminate staticity, while Neutrosophic Calculus is the mathematics of…

General Mathematics · Mathematics 2015-09-28 Florentin Smarandache

In mathematics information is a number that measures uncertainty (entropy) based on a probabilistic distribution, often of an obscure origin. In real life language information is a datum, a statement, more precisely, a formula. But such a…

Artificial Intelligence · Computer Science 2022-05-17 Anatol Slissenko

Symbolic (or Literal) Neutrosophic Theory is referring to the use of abstract symbols (i.e. the letters T, I, F, or their refined indexed letters Tj, Ik, Fl) in neutrosophics. We extend the dialectical triad thesis-antithesis-synthesis to…

Artificial Intelligence · Computer Science 2015-12-02 Florentin Smarandache

Misinformation is still a major societal problem and the arrival of Large Language Models (LLMs) only added to it. This paper analyzes synthetic, false, and genuine information in the form of text from spectral analysis, visualization, and…

Artificial Intelligence · Computer Science 2024-07-09 Vishnu S. Pendyala , Madhulika Dutta

Real-valued logics underlie an increasing number of neuro-symbolic approaches, though typically their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of…

Logic in Computer Science · Computer Science 2022-09-01 Ronald Fagin , Ryan Riegel , Alexander Gray

The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. At first the concept of fuzzy Datalog will be summarized, then its extensions for…

Artificial Intelligence · Computer Science 2010-04-08 Agnes Achs

In this paper a knowledge representation model are proposed, FP5, which combine the ideas from fuzzy sets and penta-valued logic. FP5 represents imprecise properties whose accomplished degree is undefined, contradictory or indeterminate for…

Artificial Intelligence · Computer Science 2015-02-20 Vasile Patrascu

An information-theoretic framework is introduced to analyze last-layer embedding, focusing on learned representations for regression tasks. We define representation-rate and derive limits on the reliability with which input-output…

Information Theory · Computer Science 2026-05-27 Deborah Pereg , Michael Wand

An interval-valued fuzzy answer set programming paradigm is proposed for nonmonotonic reasoning with vague and uncertain information. The set of sub-intervals of $[0,1]$ is considered as truth-space. The intervals are ordered using…

Artificial Intelligence · Computer Science 2020-08-06 Sandip Paul , Kumar Sankar Ray , Diganta Saha

In this paper, we first give the cartesian product of two neutrosophic multi sets(NMS). Then, we define relations on neutrosophic multi sets to extend the intuitionistic fuzzy multi relations to neutrosophic multi relations. The relations…

Logic · Mathematics 2015-06-15 Said Broumi , Irfan Deli , Florentin Smarandache

In this paper two knowledge representation models are proposed, FP4 and FP6. Both combine ideas from fuzzy sets and four-valued and hexa-valued logics. Both represent imprecise properties whose accomplished degree is unknown or…

Computer Vision and Pattern Recognition · Computer Science 2015-02-20 Vasile Patrascu

It is proposed a complex valued channel encoding for multidimensional data. The basic approach contains overlapping of complex nonlinear mappings. Its development leads to sparse representation of multi-channel data, increasing their…

Computer Vision and Pattern Recognition · Computer Science 2013-10-02 P. A. Golovinski , V. A. Astapenko

As machine learning models are increasingly considered for high-stakes domains, effective explanation methods are crucial to ensure that their prediction strategies are transparent to the user. Over the years, numerous metrics have been…

Machine Learning · Computer Science 2025-04-14 Johannes Maeß , Grégoire Montavon , Shinichi Nakajima , Klaus-Robert Müller , Thomas Schnake