A Study of Network Theory Using Graph-Theoretic Approaches
Network theory has great significance in the assessment of complex systems in various domains such as computer science, biology, social sciences, and communication systems. This research paper provides a detailed discussion of network theory through the application of graph theory methods to assess networks and analyse interconnected systems. Graph theory is a branch of mathematics in which nodes represent entities and edges represent the relationships between them. Various aspects of graph theory, such as graph representation, connectivity, centrality measures, clustering behavior, and shortest path algorithms, are discussed to assess network performance. Additionally, popular network models, including random, small-world, and scale-free networks, are discussed. The practical applications of network theory in several domains, such as social networks, transportation systems, biological networks, and communication systems, are also covered in this research paper. Experimental analysis on benchmark datasets proves that the use of a graph-theoretic approach enhances the efficiency of the network analysis process and simplifies the identification of influential nodes within a network.