Mandelbrot Law of Evolving Networks

An Evolving model of online bipartite networks

Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shi...

The Asymptotic Mandelbrot Law of Some Evolution Networks

Complex networks are now the joint focus of many branches of research. Particularly, the scale-free property of some networks attracts continuous interests, due to their importance and pervasiveness. In short, this property means that the degree distribution of a network obeys a power law P (k) ∝ k , where k is the degree and P (k) is the corresponding probability density, and the scaling expon...

On the Analysis of Queues with Heavy Tails: A Non-Extensive Maximum Entropy Formalism and a Generalisation of the Zipf-Mandelbrot Distribution

A critique of a non-extensive maximum entropy (NME) formalism is undertaken in conjunction with its application into the analysis of queues with heavy tails that are often observed in performance evaluation studies of heterogeneous networks exhibiting traffic burstiness, self-similarity and/or long range dependence (LRD). The credibility of the NME formalism, as a method of inductive inference,...

Scale-invariant statistics of the degrees of separation in directed earthquake network

Discovery of a new scale-free law of earthquake phenomenon is reported. It is relevant to the structural and dynamical properties of the earthquake network proposed in a recent work [S. Abe and N. Suzuki, Europhys. Lett. 65, 581 (2004)]. The seismic data taken in southern California are mapped to an evolving directed network. It is found that statistics of the degrees of separation between two ...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation