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Springer Fuzzy Graph Theory - Studies in Fuzziness 363

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Description

Explore the fundamentals of fuzzy graph theory with this academic text from Springer. Part of the Studies in Fuzziness and Soft Computing series, volume 363 provides a timely overview designed to build a foundation for future applications across various scientific fields. Readers will gain a deep understanding of essential theories, including Craine's work on fuzzy interval graphs and fuzzy analogs of Marczewski's theorem. The text covers the Gilmore and Hoffman characterization, as well as the Fulkerson and Gross characterization and Menger's theorem. This volume also provides detailed discussions on core concepts such as connectivity, distance, and saturation in fuzzy graphs, making it an essential resource for those studying computer science, AI, and machine learning.

Key Features

This Springer publication serves as a foundational text for understanding fuzzy graph theory and its future applications.

The book covers fundamental theories including Craine's work on fuzzy interval graphs and fuzzy analogs of Marczewski's theorem.

Detailed technical content includes the Gilmore and Hoffman characterization alongside the Fulkerson and Gross characterization.

Learn about Menger's theorem and its related applications within the field of fuzzy graph theory.

The text provides in-depth discussions on vital concepts like connectivity, distance, and saturation in fuzzy graphs.

Product Specifications

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

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