KEYWORDS: Modeling, Systems modeling, Mathematical modeling, Internet, Numerical simulations, Computer simulations, Social networks, Process modeling, Statistical modeling, Data modeling
Real-world complex networks such the Internet, social networks and biological networks have increasingly attracted
the interest of researchers from many areas. Accurate modelling of the statistical regularities of these
large-scale networks is critical to understand their global evolving structures and local dynamical patterns. Two
main families of models have been widely studied: those based on the Erdos and Renyi random graph model
and those on the Barabasi-Albert scale-free model. In this paper we develop a new model: the Hybrid model,
which incorporates two stages of growth. The aim of this model is to simulate the transition process between a
static randomly connected network and a growing scale-free network through a tuning parameter. We measure
the Hybrid model by extensive numerical simulations, focusing on the critical transition point from Poisson to
Power-law degree distribution.
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