activity
20062018
most citedPhase transition of a one-dimensional Ising model with distance-dependent connections

7 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DL2018

The efficiency of community detection by most similar node pairs

Yunfeng Chang, Jihui Han

Community analysis is an important way to ascertain whether or not a complex system consists of sub-structures with different properties. In this paper, we give a two level communi…

physics.soc-ph2017★ 1 cited

The way to uncover community structure with core and diversity

YunFeng Chang, SeungKee Han, XiDong Wang

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity…

nlin.PS2007★ 7 cited

Phase transition of a one-dimensional Ising model with distance-dependent connections

YunFeng Chang, Liang Sun, Xu Cai

The critical behavior of Ising model on a one-dimensional network, which has long-range connections at distances with the probability , is studied by using M…

nlin.PS2006★ 3 cited

The macro-behavior of agents' opinion under the influence of an external field

YunFeng Chang, Long Guo, Xu Cai

In this paper, a model about the evolution of opinion on small world networks is proposed. We studied the macro-behavior of the agents' opinion and the relative change rate as time…

nlin.AO2006

A self-organized particle moving model on scale free network with behavior

YunFeng Chang, Long Guo, Xu Cai

In this paper we propose a self-organized particle moving model on scale free network with the algorithm of the shortest path and preferential walk. The over-capacity property of t…

nlin.AO2006★ 1 cited

Theoretical analysis and multi-agent simulation of the ecosystem in Tibet

YunFeng Chang, BoJin Zheng, Long Guo +1

Bird Funeral is a strange funeral custom in Tibet of China. The lamaists hope they can save small fauna such as pikas by sacrificing themselves to the eagles. But can they save the…