activity
20142026
most citedTsallis information dimension of complex networks

35 citations · 69 across the 14 of their papers we have counts for

collaborators

14 papers

physics.soc-ph2026

Evidential Reconstruction of Network from Time Series

Yishu Xian, Zhaobo Zhang, Cai Zhang +2

Reconstructing the topology of complex networks from observational data remains a central challenge in network science. Here we propose a framework that is based on the Dempster-Sh…

physics.soc-ph2024

Structural analysis and the sum of nodes' betweenness centrality in complex networks

Ronghao Deng, Meizhu Li, Qi Zhang

Structural analysis in network science is finding the information hidden from the topology structure of complex networks. Many methods have already been proposed in the research on…

cond-mat.stat-mech2023

Ensemble equivalence and asymptotic equipartition property in information theory

Meizhu Li, Qi Zhang

There is a consensus in science that information theory and statistical physics have a close relationship but the literary proofs of the equivalence between most of the conceptions…

cond-mat.stat-mech2022

Local entropy and nonextensivity of networks ensembles

Qi Zhang, Meizhu Li

Nonextensivity is foreseeable in network ensembles, as heterogeneous interactions generally exist in complex networked systems that need to be described by network ensembles. But t…

cs.SI2015★ 1 cited

Measure the similarity of nodes in the complex networks

Qi Zhang, Meizhu Li, Yong Deng +1

Measure the similarity of the nodes in the complex networks have interested many researchers to explore it. In this paper, a new method which is based on the degree centrality and…

cs.SI2015★ 1 cited

Nonextensive analysis on the local structure entropy of complex networks

Qi Zhang, Meizhu Li, Yuxian Du +2

The local structure entropy is a new method which is proposed to identify the influential nodes in the complex networks. In this paper a new form of the local structure entropy of…

cs.SI2015

Tsallis entropy of complex networks

Qi Zhang, Meizhu Li, Yong Deng +1

How complex of the complex networks has attracted many researchers to explore it. The entropy is an useful method to describe the degree of the of the complex networks. I…

cs.SI2015★ 2 cited

Identification of influential nodes in network of networks

Meizhu Li, Qi Zhang, Qi Liu +1

The network of networks(NON) research is focused on studying the properties of n interdependent networks which is ubiquitous in the real world. Identifying the influential nodes in…

cs.SI2014★ 20 cited

Local structure entropy of complex networks

Qi Zhang, Meizhu Li, Yuxian Du +1

Identifying influential nodes in the complex networks is of theoretical and practical significance. There are many methods are proposed to identify the influential nodes in the com…

cs.SI2014★ 4 cited

A new structure entropy of complex networks based on Tsallis nonextensive statistical mechanics

Qi Zhang, Xi Lu, Meizhu Li +2

The structure entropy is one of the most important parameters to describe the structure property of the complex networks. Most of the existing struc- ture entropies are based on th…

cs.SI2014★ 5 cited

A betweenness structure entropy of complex networks

Qi Zhang, Meizhu Li, Yong Deng

The structure entropy is an important index to illuminate the structure property of the complex network. Most of the existing structure entropies are based on the degree distributi…

cs.AI2014★ 1 cited

Multiscale probability transformation of basic probability assignment

Meizhu Li, Qi Zhang, Yong Deng

Decision making is still an open issue in the application of Dempster-Shafer evidence theory. A lot of works have been presented for it. In the transferable belief model (TBM), pig…

cs.SI2014★ 35 cited

Tsallis information dimension of complex networks

Qi Zhang, Meizhu Li, Yong Deng +1

The fractal and self-similarity properties are revealed in many complex networks. In order to show the influence of different part in the complex networks to the information dimens…

cs.AI2014

Distance function of D numbers

Meizhu Li, Qi Zhang, Xinyang Deng +1

Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic proba…