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010   $a3-031-39756-8
024 7 $a10.1007/978-3-031-39756-1
035   $a(MiAaPQ)EBC30716857
035   $a(Au-PeEL)EBL30716857
035   $a(DE-He213)978-3-031-39756-1
035   $a(PPN)272260525
035   $a(CKB)28008128100041
035   $a(EXLCZ)9928008128100041
100   $a20230820d2023      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aWeighted and Fuzzy Graph Theory /$fby Sunil Mathew, John N. Mordeson, M. Binu
205   $a1st ed. 2023.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023.
215   $a1 online resource (226 pages)
225 1 $aStudies in Fuzziness and Soft Computing,$x1860-0808 ;$v429
311 08$aPrint version: Mathew, Sunil Weighted and Fuzzy Graph Theory Cham : Springer,c2023 9783031397554 
327   $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.
330   $aOne of the most preeminent ways of applying mathematics in real-world scenario modeling involves graph theory. A graph can be undirected or directed depending on whether the pairwise relationships among objects are symmetric or not. Nevertheless, in many real-world situations, representing a set of complex relational objects as directed or undirected is not su¢ cient. Weighted graphs o§er a framework that helps to over come certain conceptual limitations. We show using the concept of an isomorphism that weighted graphs have a natural connection to fuzzy graphs. As we show in the book, this allows results to be carried back and forth between weighted graphs and fuzzy graphs. This idea is in keeping with the important paper by Klement and Mesiar that shows that many families of fuzzy sets are lattice isomorphic to each other. We also outline the important work of Head and Weinberger that show how results from ordinary mathematics can be carried over to fuzzy mathematics. We focus on the concepts connectivity, degree sequences and saturation, and intervals and gates in weighted graphs.
410  0$aStudies in Fuzziness and Soft Computing,$x1860-0808 ;$v429
606   $aComputational intelligence
606   $aGraph theory
606   $aComputational Intelligence
606   $aGraph Theory
615  0$aComputational intelligence.
615  0$aGraph theory.
615 14$aComputational Intelligence.
615 24$aGraph Theory.
676   $a006.3
700   $aMathew$b Sunil$01061654
701   $aMordeson$b John N$063000
701   $aBinu$b M$01424070
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910741189003321
996   $aWeighted and Fuzzy Graph Theory$93552948
997   $aUNINA