Neutrosophic Theories in Communication, Management and Information Technology


Florentin Smarandache, PhD (Editor)
Department of Mathematics and Sciences, University of New Mexico, New Mexico, USA

Broumi Said (Editor)
Laboratory of Information Processing, Faculty of Science Ben M’Sik, University Hassan II Casablanca, Morocco

Series: Mathematics Research Developments
BISAC: MAT027000

Contributing to the fast growing new field of neutrosophy, this book provides a significant collection of unedited articles covering the latest ongoing research area. Neutrosopy is above all a new view on modelling, tailored to effectively address the uncertainties inherent of the real world. In short, Neutrosophy supersedes in logics the binary approach of true or false by introducing a third state: neutral, which can be also interpreted as indeterminate, uncertain, inconsistent …. Development of neutrosophy since its conception by Smarandache in 1988 exponentially grows by conceptual extensions of logics, measure, sets, graphs, as well as practical applications in namely all fields. It can be think as generalization of fuzzy logic and its variants like intuitionistic fuzzy logic.
Registered in wide collection of books on this promising field, here we deliver to researchers, lecturers and postgraduate students pursuing research on neutrosophic a set of eighteen unreleased articles on state of the art theoretical developments, applications and understanding of neutrosophy. This volume complements the reference works of the founder and extend the already numerous books of this editor on the subject. This book starts by describing a major application of neutrosophy: product acceptance determination using a similarity measure index by applying neutrosophic statistics. In one the latest leading mathematics branch: Graph theory, we provide an article on neutrosophic extension of graphs that we can call a neutrosophic graph. A reflection is given on the true nature of neutrosophy by exploring its link with learning such as by Artificial Neural Networks, including Deep Learning. Again, in Mathematics a discussion is made on the solving of systems of linear equations in neutrosophic representation. We also go to the opposite of theory, down to the practical details of implementation for topology using the C# language. Neutrosophic probability is another big new research field. Here, we present a study on the advantages of using neutrosophic variables.
Other discipline such as algebra, topology, decision making as well as problem as in logistics and transport are concerned by the remaining articles. Last but not least, we would like to finally mention a major paper to conclude this short presentation of our book titled «When Neutrosophic Theory Meets Three-Way Decisions».
(Imprint: Nova)

Table of Contents

Table of Contents



Chapter 1. Product Acceptance Determination Using Similarity Measure Index by Neutrosophic Statistics
(Muhammad Aslam and Rehan Ahmed Khan Sherwani, Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia, and others)

Chapter 2. New Concepts of Strongly Edge Irregular Interval-Valued Neutrosophic Graphs
(A. A.Talebi, Hossein Rashmanlou and Masoomeh Ghasemi, Department of Mathematics, University of Mazandaran, Babolsar, Iran)

Chapter 3. The Link between Neutrosophy and Learning: Through the Related Concepts of Representation and Compression
(Philippe Schweizer, Independent Researcher, Morges, Switzerland)

Chapter 4. Neutrosophic Soft Cubic M-Subalgebras of B-Algebras
(Mohsin Khalid, Neha Andaleeb Khalid and Hasan Khalid, Department of Mathematics and Statistics, The University of Lahore, Lahore, Pakistan, and others)

Chapter 5. Alpha, Beta and Gamma Product of Neutrosophic Graphs
(Nasir Shah, Said Broumi, Abdul Raheem and Tahir Imran)

Chapter 6. Neutrosophic Cubic Normal Ideal and Neutrosophic Cubic Closed Normal Ideal of PS-Algebra
(Mohsin Khalid, Hasan khalid and Neha Andaleeb Khalid, Department of Mathematics and Statistics, University of Lahore, Lahore, Pakistan, and others)

Chapter 7. Neutrosophic Multisets: An Overview
(Vakkas Uluçay, Araban, Gaziantep, Turkey)

Chapter 8. Neutrosophy as a Model for Knowledge: The Influence of Representative Models on Thinking
(Philippe Schweizer, Independent Researcher, Morges, Switzerland)

Chapter 9. When Neutrosophic Theory Meets Three-Way Decisions
(Rui Ren, Chao Zhang and Deyu Li, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, School of Computer and Information Technology, Shanxi University,
Achievement Transformation Co., Ltd of Shanxi Transition and Comprehensive Reform Demonstration Zone Shanxi, China)

Chapter 10. Neutrosophic Economic Order Quantity Model with More Than One Price Breaks
(R. Surya, M. Mullai and G. Madhan Kumar, Department of Mathematics, Alagappa University, Karaikudi, Tamilnadu, India)

Chapter 11. General Non-Square Systems of Linear Equations in Single-Valued Triangular Neutrosophic Number Environment
(S. A. Edalatpanah, Department of Research Center, Ayandegan Institute of Higher Education, Tonekabon, Iran)

Chapter 12. Hesitant Neutrosophic Soft Set Relations
(Abhijit Saha, Deptartments of Mathematics, Techno College of Engg, Agartala, Tripura, India

Chapter 13. Computer Application of Neutrosophic Set Operations
(S. Saranya, M. Vigneshwaran, Said Broumi, Research Department of Mathematics, Kongunadu Arts and Science College, Coimbatore, Tamilnadu, India

Chapter 14. Triangular Bipolar Neutrosophic Based Transportation Problem
(Avishek Chakraborty, Department of Basic Science, Narula Institute of Technology, Agarpara, Kolkata, India, and others)

Chapter 15. Studying Neutrosophic Variables
(Rafif Alhabib and Ahmad Salama, Department of Mathematical Statistics, Faculty of Science, Albaath University, Syria)

Chapter 16. Decision Making for Logistics Center Location Selection in Trapezoidal Neutrosophic Environment
(Kalyan Mondal and Surapati Pramanik, Department of Mathematics, Jadavpur University, Kolkata, West Bengal, India, and others)

Chapter 17. Weighted Similarity Measure and Decision Making Model for Clinical Application of Single Valued Neutrosophic Set
(R.Binu and P. Isaac, Department of Mathematics, Rajagiri School of Engineering and Technology, Ernakulam, Kerala, India)

Chapter 18. Rough Neutrosophic Set: An Overview
(Surapati Pramanik, Department of Mathematics, Nandalal Ghosh B.T. College, Panpur, Narayanpur, Parganas, West Bengal, India)

Chapter 19. Some New Concepts on Normalized SVTN-Numbers and Multiple Criteria Decision Making
(İrfan Deli and Emel Kırmızı Öztürk, Muallim Rıfat Faculty of Education, Aralık University, Kilis, Turkey, and others)


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