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020 _a9783031397561
_9978-3-031-39756-1
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_223
100 1 _aMathew, Sunil.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aWeighted and Fuzzy Graph Theory
_h[electronic resource] /
_cby Sunil Mathew, John N. Mordeson, M. Binu.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXVII, 216 p. 92 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1860-0808 ;
_v429
500 _aAcceso multiusuario
505 0 _aGraphs and Weighted Graphs -- Connectivity -- More on Connectivity -- Cycle Connectivity -- Distance and Convexity -- Degree Sequences and Saturation -- Intervals and Gates -- Weighted Graphs and Fuzzy Graphs -- Fuzzy Results from Crisp Results.
520 _aOne of the most preeminent ways of applying mathematics in real-world scenario modeling involves graph theory. A graph can be undirected or directed depending on whether the pairwise relationships among objects are symmetric or not. Nevertheless, in many real-world situations, representing a set of complex relational objects as directed or undirected is not su¢ cient. Weighted graphs o§er a framework that helps to over come certain conceptual limitations. We show using the concept of an isomorphism that weighted graphs have a natural connection to fuzzy graphs. As we show in the book, this allows results to be carried back and forth between weighted graphs and fuzzy graphs. This idea is in keeping with the important paper by Klement and Mesiar that shows that many families of fuzzy sets are lattice isomorphic to each other. We also outline the important work of Head and Weinberger that show how results from ordinary mathematics can be carried over to fuzzy mathematics. We focus on the concepts connectivity, degree sequences and saturation, and intervals and gates in weighted graphs.
541 _fUABC ;
_cPerpetuidad
650 0 _aComputational intelligence.
650 0 _aGraph theory.
650 1 4 _aComputational Intelligence.
650 2 4 _aGraph Theory.
700 1 _aMordeson, John N.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aBinu, M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031397554
776 0 8 _iPrinted edition:
_z9783031397578
776 0 8 _iPrinted edition:
_z9783031397585
830 0 _aStudies in Fuzziness and Soft Computing,
_x1860-0808 ;
_v429
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-39756-1
912 _aZDB-2-INR
912 _aZDB-2-SXIT
942 _cLIBRO_ELEC
999 _c262216
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