Data analytics and networking are inherently interdependent, as effective data collection, transmission, and processing rely on robust and optimally configured network infrastructures. Real-world networks are often characterized by uncertainty, vagueness, and dynamic constraints, necessitating advanced mathematical tools beyond classical graph-theoretic approaches. This book presents a comprehensive framework for optimal network analysis using vertex order coloring under fuzzy, intuitionistic fuzzy, and neutrosophic graph environments. Novel methodologies based on fuzzy vertex order coloring (FVOC), intuitionistic fuzzy vertex order coloring (IFVOC), and neutrosophic vertex order coloring are developed to identify and classify α-strong, β-strong, and γ-strong vertices, enabling systematic analysis and comparison of network robustness and efficiency. Various graph product operations, including co-normal, modular, residue, maximal, and related products are rigorously analyzed to determine optimal network configurations using key performance metrics such as chromatic number, distribution and weight of strong vertices, and minimum spanning tree weight.
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Paperback. Condition: new. Paperback. Data analytics and networking are inherently interdependent, as effective data collection, transmission, and processing rely on robust and optimally configured network infrastructures. Real-world networks are often characterized by uncertainty, vagueness, and dynamic constraints, necessitating advanced mathematical tools beyond classical graph-theoretic approaches. This book presents a comprehensive framework for optimal network analysis using vertex order coloring under fuzzy, intuitionistic fuzzy, and neutrosophic graph environments. Novel methodologies based on fuzzy vertex order coloring (FVOC), intuitionistic fuzzy vertex order coloring (IFVOC), and neutrosophic vertex order coloring are developed to identify and classify a-strong, b-strong, and g-strong vertices, enabling systematic analysis and comparison of network robustness and efficiency. Various graph product operations, including co-normal, modular, residue, maximal, and related products are rigorously analyzed to determine optimal network configurations using key performance metrics such as chromatic number, distribution and weight of strong vertices, and minimum spanning tree weight. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786209583803
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data analytics and networking are inherently interdependent, as effective data collection, transmission, and processing rely on robust and optimally configured network infrastructures. Real-world networks are often characterized by uncertainty, vagueness, and dynamic constraints, necessitating advanced mathematical tools beyond classical graph-theoretic approaches. This book presents a comprehensive framework for optimal network analysis using vertex order coloring under fuzzy, intuitionistic fuzzy, and neutrosophic graph environments. Novel methodologies based on fuzzy vertex order coloring (FVOC), intuitionistic fuzzy vertex order coloring (IFVOC), and neutrosophic vertex order coloring are developed to identify and classify ¿-strong, ß-strong, and ¿-strong vertices, enabling systematic analysis and comparison of network robustness and efficiency. Various graph product operations, including co-normal, modular, residue, maximal, and related products are rigorously analyzed to determine optimal network configurations using key performance metrics such as chromatic number, distribution and weight of strong vertices, and minimum spanning tree weight.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch. Seller Inventory # 9786209583803
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Taschenbuch. Condition: Neu. Vertex Order Coloring in Fuzzy Graphs and its Applications | A. Meenakshi (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209583803 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Seller Inventory # 134572345
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