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Fuzzy Graph Theory (Studies in Fuzziness and Soft Computing) de Sunil Mathew,John N. Mordeson,Davender S. Malik
Descripción - Reseña del editor This book provides a timely overview of fuzzy graph theory, laying the foundation for future applications in a broad range of areas. It introduces readers to fundamental theories, such as Craine’s work on fuzzy interval graphs, fuzzy analogs of Marczewski’s theorem, and the Gilmore and Hoffman characterization. It also introduces them to the Fulkerson and Gross characterization and Menger’s theorem, the applications of which will be discussed in a forthcoming book by the same authors. This book also discusses in detail important concepts such as connectivity, distance and saturation in fuzzy graphs. Thanks to the good balance between the basics of fuzzy graph theory and new findings obtained by the authors, the book offers an excellent reference guide for advanced undergraduate and graduate students in mathematics, engineering and computer science, and an inspiring read for all researchers interested in new developments in fuzzy logic and applied mathematics. Contraportada This book provides a timely overview of fuzzy graph theory, laying the foundation for future applications in a broad range of areas. It introduces readers to fundamental theories, such as Craine’s work on fuzzy interval graphs, fuzzy analogs of Marczewski’s theorem, and the Gilmore and Hoffman characterization. It also introduces them to the Fulkerson and Gross characterization and Menger’s theorem, the applications of which will be discussed in a forthcoming book by the same authors. This book also discusses in detail important concepts such as connectivity, distance and saturation in fuzzy graphs.Thanks to the good balance between the basics of fuzzy graph theory and new findings obtained by the authors, the book offers an excellent reference guide for advanced undergraduate and graduate students in mathematics, engineering and computer science, and an inspiring read for all researchers interested in new developments in fuzzy logic and applied mathematics. Biografía del autor Dr. Sunil Mathew is currently a Faculty Member in the Department of Mathematics, NIT Calicut, India. He has acquired his masters from St. Joseph’s College Devagiri, Calicut, and Ph.D. from National Institute of Technology Calicut in the area of Fuzzy Graph Theory. He has published more than 75 research papers and written two books. He is a member of several academic bodies and associations. He is editor and reviewer of several international journals. He has an experience of 20 years in teaching and research. His current research topics include fuzzy graph theory, bio-computational modeling, graph theory, fractal geometry, and chaos. Dr. John N. Mordeson is Professor Emeritus of Mathematics at Creighton University. He received his B.S., M.S., and Ph.D. from Iowa State University. He is a Member of Phi Kappa Phi. He is the President of the Society for Mathematics of Uncertainty. He has published 15 books and 200 journal articles. He is on the editorial board of numerous journals. He has served as an external examiner of Ph.D. candidates from India, South Africa, Bulgaria, and Pakistan. He has refereed for numerous journals and granting agencies. He is particularly interested in applying mathematics of uncertainty to combat the problem of human trafficking. Dr. Davender S. Malik is a Professor of Mathematics at Creighton University. He received his Ph.D. from Ohio University and has published more than 55 papers and 18 books on abstract algebra, applied mathematics, graph theory, fuzzy automata theory and languages, fuzzy logic and its applications, programming, data structures, and discrete mathematics.
Detalles del Libro
- Name: Fuzzy Graph Theory (Studies in Fuzziness and Soft Computing)
- Autor: Sunil Mathew,John N. Mordeson,Davender S. Malik
- Categoria: Libros,Ciencias, tecnología y medicina,Matemáticas
- Tamaño del archivo: 12 MB
- Tipos de archivo: PDF Document
- Descargada: 125 times
- Idioma: Español
- Archivos de estado: AVAILABLE
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Fuzzy Graphs / SpringerLink ~ Cite this chapter as: Mathew S., Mordeson J.N., Malik D.S. (2018) Fuzzy Graphs. In: Fuzzy Graph Theory. Studies in Fuzziness and Soft Computing, vol 363.
Studies in Fuzziness and Soft Computing - Springer ~ The series “Studies in Fuzziness and Soft Computing” contains publications on various topics in the area of soft computing, which include fuzzy sets, rough sets, neural networks, evolutionary computation, probabilistic and evidential reasoning, multi-valued logic, and related fields.
Fuzzy Graph Theory / Sunil Mathew / Springer ~ This book provides a timely overview of fuzzy graph theory, laying the foundation for future applications in a broad range of areas. It introduces readers to fundamental theories, such as Craine’s work on fuzzy interval graphs, fuzzy analogs of Marczewski’s theorem, and the Gilmore and Hoffman characterization.
Fuzzy Soft Graphs / SpringerLink ~ We describe the notions of fuzzy soft trees, fuzzy soft cycles, fuzzy soft bridges, fuzzy soft cutnodes and investigate some of their fundamental properties. We also discuss some types of arcs in fuzzy soft graphs. We describe applications of fuzzy soft graphs in social network and road network. This chapter is due to [28, 30, 48].
Advanced Topics in Fuzzy Graph Theory (Studies in ~ Advanced Topics in Fuzzy Graph Theory (Studies in Fuzziness and Soft Computing) 1st ed. 2019 Edition by John N. Mordeson (Author), Sunil Mathew (Author) ISBN-13: 978-3030042141
Fuzzy mathematics - Wikipedia ~ Fuzzy mathematics forms a branch of mathematics related to fuzzy set theory and fuzzy logic.It started in 1965 after the publication of Lotfi Asker Zadeh's seminal work Fuzzy sets. A fuzzy subset A of a set X is a function A:X→L, where L is the interval [0,1]. This function is also called a membership function. A membership function is a generalization of a characteristic function or an .
Fuzzy Graphs and Fuzzy Hypergraphs (Studies in Fuzziness ~ Buy Fuzzy Graphs and Fuzzy Hypergraphs (Studies in Fuzziness and Soft Computing) on FREE SHIPPING on qualified orders Skip to main content Hello, Sign in. Account & Lists Sign in Account . fuzzy graph theory was identified quite early on for its importance in making things work.
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Advanced topics in fuzzy graph theory (eBook, 2019 ~ Get this from a library! Advanced topics in fuzzy graph theory. [John N Mordeson; Sunil Mathew] -- This book builds on two recently published books by the same authors on fuzzy graph theory. Continuing in their tradition, it provides readers with an extensive set of tools for applying fuzzy .
Fuzzy Graph Theory / Springer for Research & Development ~ This book provides a timely overview of fuzzy graph theory, laying the foundation for future applications in a broad range of areas. It introduces readers to fundamental theories, such as Craine’s work on fuzzy interval graphs, fuzzy analogs of Marczewski’s theorem, and the Gilmore and Hoffman characterization.
Fuzzy Graphs and Fuzzy Hypergraphs - John N. Mordeson ~ In the course of fuzzy technological development, fuzzy graph theory was identified quite early on for its importance in making things work. Two very important and useful concepts are those of granularity and of nonlinear ap proximations. The concept of granularity has evolved as a cornerstone of Lotfi A.Zadeh's theory of perception, while the concept of nonlinear approx imation is the driving .
(Studies in Fuzziness and Soft Computing 316) Pankaj Gupta ~ aaa
Certain Algorithms for Computing Strength of Competition ~ Fuzzy graph theory is one of the most developing area of research, which has a variety of applications in different fields, including computer science, communication networks, biological sciences, social networks, decision-making and optimization problems.
Fuzzy Graph Theory with Applications to Human Trafficking ~ This book reports on advanced concepts in fuzzy graph theory, showing a set of tools that can be successfully applied to understanding and modeling illegal human trafficking. Building on the previous
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Fuzzy Graph Structures with Application - MDPI ~ Fuzzy Graph Structures with Application Muzzamal Sitara 1, . introduced fuzzy graphs using Zadeh’s fuzzy relation [4]. Fuzzy-graph theory is growing rapidly, with numerous applications in . the degree of vertex in some fuzzy graphs. Akram et al. [17–20] defined certain notions of soft graphs, bipolar fuzzy graphs, and hypergraphs .
Fuzzy soft graphs with applications - IOS Press ~ A fuzzy soft set is a mapping from parameter set to the fuzzy subsets of universe. Fuzzy soft set theory provides a parameterized point of view for uncertainty modeling and soft computing model. In this research article, we apply the concept of fuzzy
5_2005Web Intelligence, WK and FL-Studies in Fuzziness and ~ 5_2005Web Intelligence, WK and FL-Studies in Fuzziness and Soft Computing-SpringerVol164-p1-18 - Free download as PDF File (.pdf), Text File (.txt) or read online for free.
CiNii 図書 - Fuzzy graphs and fuzzy hypergraphs ~ Fuzzy graphs and fuzzy hypergraphs John N. Mordeson, Premchand S. Nair （Studies in fuzziness and soft computing, v. 46） Physica-Verlag, c2000
(PDF) Fuzzy Graph Theory, A survey - ResearchGate ~ A fuzzy graph G is a pair (σ,μ) where σ is a fuzzy subset of S and μ is a fuzzy relation on S such that μ(u,v)≤σ(u)∧σ(v). In this paper, the center problems on fuzzy graphs are studied.
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Graph Analytics, Fuzzy Graph Theory, Causality, Decision ~ Graph Analytics, Fuzzy Graph Theory, Causality, Decision Support and Data Science martes, 28 de julio de 2015. From my course of flexible methods for data querying and knowledge discovery Publicado por Maikel Leyva en . Soft Computing for Business Intelligence.
Trends in Fuzzy Graphs / Open Access Journals ~ After introducing and developing fuzzy set theory, a lot of studies have been done in this field and then a result appeared as a Fuzzy Graph (Combination of graph theory and fuzzy set theory). This is now known as Fuzzy graph theory. In this article we review essential works on different types of fuzzy graph and fuzzy hyper graph.
Chapter 4, Neuro-Fuzzy and Soft Computing: Fuzzy Inference ~ Neuro-Fuzzy and Soft Computing: Fuzzy Sets 3 Introduction (4.1)Introduction (4.1) Fuzzy inference is a computer paradigm based on fuzzy set theory, fuzzy if-then-rules and fuzzy reasoning Applications: data classification, decision analysis, expert systems, times series predictions, robotics & pattern recognition
(PDF) Studies on Fuzzy Graphs - ResearchGate ~ Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems.