Classic Complex Network BA Model
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Resource Overview
Implementation of the classical Barabási–Albert (BA) model for complex networks, featuring degree distribution visualization capabilities.
Detailed Documentation
This is an implementation of the classical Barabási–Albert (BA) model for complex networks, which generates scale-free networks and visualizes their degree distributions. The degree distribution plot serves as a crucial tool for understanding node connectivity patterns within network structures. By analyzing the degree distribution, we can identify whether hub nodes exist in the network topology. The BA model employs a preferential attachment algorithm where new nodes are more likely to connect to existing nodes with higher degrees, simulating real-world network growth mechanisms. This model can generate topological structures resembling real-world networks, aiding researchers in better understanding network dynamics in practical scenarios. The implementation typically involves node initialization, iterative attachment processes, and degree calculation functions to construct the network and plot the distribution.
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