Special Issue "Neutrosophic Information Theory and Applications"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Theory and Methodology".

Deadline for manuscript submissions: 15 February 2018

Special Issue Editors

Guest Editor
Prof. Dr. Florentin Smarandache

Department of Mathematics and Sciences, University of New Mexico, 705 Gurley Ave., Gallup, NM 87301, USA
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Interests: artificial intelligence; quantum physics; number theory; statistics; algebraic structures
Guest Editor
Prof. Jun Ye

Department of Electrical and Information Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing 312000, China
Website | E-Mail
Interests: soft computing; fuzzy decision theory and method; robot intelligent control; pattern recognition and fault diagnosis; neutrosophic theory; rock mechanics; engineering modeling; optimization design

Special Issue Information

Dear Colleagues,

Neutrosophic logic, symbolic logic, set, probability, statistics, etc., are, respectively, generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on.

Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. A number of new netrosophic theories have been proposed and have been applied in computational intelligence, mutiple attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc.

This Special Issue invites original research papers that report on the state-of-the-art and recent advancements in neutrosophic information theory to soft computing, artificial intelligence, big and small data mining, decision making problems, pattern recognition, information processing, image processing, and many other practical achievements.

Prof. Dr. Florentin Smarandache
Prof. Jun Ye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Neutrosophic logic
  • Neutrosophic symbolic logic
  • Neutrosophic set
  • Neutrosophic probability
  • Neutrosophic statistics
  • Neutrosophic measure
  • Neutrosophic linguistic theory
  • Artificial intelligence
  • Neutrosophic image processing
  • Neutrosophic information processing
  • Neutrosophic decision making
  • Neutrosophic data mining
  • Neutrosophic decision support systems
  • Neutrosophic computational modelling
  • Neutrosophic medical diagnosis
  • Neutrosophic fault diagnosis

Published Papers (5 papers)

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Research

Open AccessArticle Neutrosophic Commutative N -Ideals in BCK-Algebras
Information 2017, 8(4), 130; doi:10.3390/info8040130
Received: 16 September 2017 / Revised: 6 October 2017 / Accepted: 16 October 2017 / Published: 18 October 2017
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Abstract
The notion of a neutrosophic commutative N -ideal in BCK-algebras is introduced, and several properties are investigated. Relations between a neutrosophic N-ideal and a neutrosophic commutative N-ideal are discussed. Characterizations of a neutrosophic commutative N-ideal are considered. Full article
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)
Open AccessArticle TODIM Method for Single-Valued Neutrosophic Multiple Attribute Decision Making
Information 2017, 8(4), 125; doi:10.3390/info8040125
Received: 20 September 2017 / Revised: 9 October 2017 / Accepted: 11 October 2017 / Published: 16 October 2017
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Abstract
Recently, the TODIM has been used to solve multiple attribute decision making (MADM) problems. The single-valued neutrosophic sets (SVNSs) are useful tools to depict the uncertainty of the MADM. In this paper, we will extend the TODIM method to the MADM with the
[...] Read more.
Recently, the TODIM has been used to solve multiple attribute decision making (MADM) problems. The single-valued neutrosophic sets (SVNSs) are useful tools to depict the uncertainty of the MADM. In this paper, we will extend the TODIM method to the MADM with the single-valued neutrosophic numbers (SVNNs). Firstly, the definition, comparison, and distance of SVNNs are briefly presented, and the steps of the classical TODIM method for MADM problems are introduced. Then, the extended classical TODIM method is proposed to deal with MADM problems with the SVNNs, and its significant characteristic is that it can fully consider the decision makers’ bounded rationality which is a real action in decision making. Furthermore, we extend the proposed model to interval neutrosophic sets (INSs). Finally, a numerical example is proposed. Full article
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)
Open AccessFeature PaperArticle Neutrosophic N-Structures Applied to BCK/BCI-Algebras
Information 2017, 8(4), 128; doi:10.3390/info8040128
Received: 12 September 2017 / Accepted: 6 October 2017 / Published: 16 October 2017
Cited by 1 | PDF Full-text (262 KB) | HTML Full-text | XML Full-text
Abstract
Neutrosophic N-structures with applications in BCK/BCI-algebras is discussed. The notions of a neutrosophic N-subalgebra and a (closed) neutrosophic N-ideal in a BCK/BCI-algebra are introduced, and several
[...] Read more.
Neutrosophic N -structures with applications in B C K / B C I -algebras is discussed. The notions of a neutrosophic N -subalgebra and a (closed) neutrosophic N -ideal in a B C K / B C I -algebra are introduced, and several related properties are investigated. Characterizations of a neutrosophic N -subalgebra and a neutrosophic N -ideal are considered, and relations between a neutrosophic N -subalgebra and a neutrosophic N -ideal are stated. Conditions for a neutrosophic N -ideal to be a closed neutrosophic N -ideal are provided. Full article
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)
Open AccessArticle Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking
Information 2017, 8(4), 122; doi:10.3390/info8040122
Received: 25 August 2017 / Revised: 29 September 2017 / Accepted: 30 September 2017 / Published: 2 October 2017
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Abstract
Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and
[...] Read more.
Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions. However, the challenge of background clutter also disturbs its performance. In this article, we propose a novel weighted histogram based on neutrosophic similarity score to help the mean-shift tracker discriminate the target from the background. Neutrosophic set (NS) is a new branch of philosophy for dealing with incomplete, indeterminate, and inconsistent information. In this paper, we utilize the single valued neutrosophic set (SVNS), which is a subclass of NS to improve the mean-shift tracker. First, two kinds of criteria are considered as the object feature similarity and the background feature similarity, and each bin of the weight histogram is represented in the SVNS domain via three membership functions T(Truth), I(indeterminacy), and F(Falsity). Second, the neutrosophic similarity score function is introduced to fuse those two criteria and to build the final weight histogram. Finally, a novel neutrosophic weighted mean-shift tracker is proposed. The proposed tracker is compared with several mean-shift based trackers on a dataset of 61 public sequences. The results revealed that our method outperforms other trackers, especially when confronting background clutter. Full article
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)
Figures

Figure 1

Open AccessFeature PaperArticle Linguistic Neutrosophic Cubic Numbers and Their Multiple Attribute Decision-Making Method
Information 2017, 8(3), 110; doi:10.3390/info8030110
Received: 25 August 2017 / Revised: 6 September 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
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Abstract
To describe both certain linguistic neutrosophic information and uncertain linguistic neutrosophic information simultaneously in the real world, this paper originally proposes the concept of a linguistic neutrosophic cubic number (LNCN), including an internal LNCN and external LNCN. In LNCN, its uncertain linguistic neutrosophic
[...] Read more.
To describe both certain linguistic neutrosophic information and uncertain linguistic neutrosophic information simultaneously in the real world, this paper originally proposes the concept of a linguistic neutrosophic cubic number (LNCN), including an internal LNCN and external LNCN. In LNCN, its uncertain linguistic neutrosophic number consists of the truth, indeterminacy, and falsity uncertain linguistic variables, and its linguistic neutrosophic number consists of the truth, indeterminacy, and falsity linguistic variables to express their hybrid information. Then, we present the operational laws of LNCNs and the score, accuracy, and certain functions of LNCN for comparing/ranking LNCNs. Next, we propose a LNCN weighted arithmetic averaging (LNCNWAA) operator and a LNCN weighted geometric averaging (LNCNWGA) operator to aggregate linguistic neutrosophic cubic information and discuss their properties. Further, a multiple attribute decision-making method based on the LNCNWAA or LNCNWGA operator is developed under a linguistic neutrosophic cubic environment. Finally, an illustrative example is provided to indicate the application of the developed method. Full article
(This article belongs to the Special Issue Neutrosophic Information Theory and Applications)

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