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Springer Fuzzy Graph Theory - Studies in Fuzziness and Soft Computing

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Description

Fuzzy Graph Theory provides a timely overview of the field, establishing a foundation for future applications across a wide range of scientific areas. As part of the Studies in Fuzziness and Soft Computing series, this book serves as an essential resource for understanding fundamental theories in computational mathematics. Readers will explore core concepts including Craine's work on fuzzy interval graphs and fuzzy analogs of Marczewski's theorem. The text also covers the Gilmore and Hoffman characterization, the Fulkerson and Gross characterization, and Menger's theorem. By studying these mathematical frameworks, learners can prepare for advanced practical applications. This volume offers detailed discussions on important concepts such as connectivity, distance, and saturation in fuzzy graphs. It is designed to guide researchers and students through the essential building blocks of fuzzy graph theory, setting the stage for upcoming developments in the field.

Key Features

Provides a comprehensive overview of fuzzy graph theory to build a strong foundation for future research and applications.

Covers fundamental theoretical works including Craine's fuzzy interval graphs and fuzzy analogs of Marczewski's theorem.

Includes detailed explanations of the Gilmore and Hoffman characterization and the Fulkerson and Gross characterization.

Explores mathematical principles such as Menger's theorem to support advanced computational studies.

Offers in-depth analysis of key concepts like connectivity, distance, and saturation in fuzzy graphs.

Part of the recognized Studies in Fuzziness and Soft Computing series by Springer.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
22 January 2018
Listed Since
19 October 2017

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