scholarly journals Recent Advances in Complex Networks Theories with Applications

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Hamid Reza Karimi ◽  
Wei Zhang ◽  
Xuebo Yang ◽  
Zhandong Yu
2012 ◽  
Vol 22 (02) ◽  
pp. 1250024 ◽  
Author(s):  
HONGCHUN WANG ◽  
KEQING HE ◽  
BING LI ◽  
JINHU LÜ

Complex software networks, as a typical kind of man-made complex networks, have attracted more and more attention from various fields of science and engineering over the past ten years. With the dramatic increase of scale and complexity of software systems, it is essential to develop a systematic approach to further investigate the complex software systems by using the theories and methods of complex networks and complex adaptive systems. This paper attempts to briefly review some recent advances in complex software networks and also develop some novel tools to further analyze complex software networks, including modeling, analysis, evolution, measurement, and some potential real-world applications. More precisely, this paper first describes some effective modeling approaches for characterizing various complex software systems. Based on the above theoretical and practical models, this paper introduces some recent advances in analyzing the static and dynamical behaviors of complex software networks. It is then followed by some further discussions on potential real-world applications of complex software networks. Finally, this paper outlooks some future research topics from an engineering point of view.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 95083-95086
Author(s):  
Jianquan Lu ◽  
Daniel W. C. Ho ◽  
Tingwen Huang ◽  
Jurgen Kurths ◽  
Ljiljana Trajkovic

2016 ◽  
Author(s):  
David Koslicki ◽  
Mark Novak

AbstractWe consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their network topology and interaction strengths are associated with uncertainty. Our primary result is the derivation of exact formulas for the expected number and probability of qualitatively incorrect predictions about a system’s responses under uncertainties drawn form arbitrary distributions of error. These formulas obviate the current use of simulations, algorithms, and qualitative modeling techniques. Additional indices provide new tools for identifying which links in a network are most qualitatively and quantitatively sensitive to error, and for determining the volume of errors within which predictions will remain qualitatively determinate (i.e. sign insensitive). Together with recent advances in the empirical characterization of uncertainty in ecological networks, these tools bridge a way towards probabilistic predictions of network dynamics.


2014 ◽  
Vol 38 (2) ◽  
pp. 184-198 ◽  
Author(s):  
Yang Tang ◽  
Feng Qian ◽  
Huijun Gao ◽  
Jürgen Kurths

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marco Guerra ◽  
Alessandro De Gregorio ◽  
Ulderico Fugacci ◽  
Giovanni Petri ◽  
Francesco Vaccarino

AbstractThe homological scaffold leverages persistent homology to construct a topologically sound summary of a weighted network. However, its crucial dependency on the choice of representative cycles hinders the ability to trace back global features onto individual network components, unless one provides a principled way to make such a choice. In this paper, we apply recent advances in the computation of minimal homology bases to introduce a quasi-canonical version of the scaffold, called minimal, and employ it to analyze data both real and in silico. At the same time, we verify that, statistically, the standard scaffold is a good proxy of the minimal one for sufficiently complex networks.


2018 ◽  
Vol 73 (2) ◽  
pp. 152-164 ◽  
Author(s):  
Deokjae Lee ◽  
B. Kahng ◽  
Y. S. Cho ◽  
K.-I. Goh ◽  
D.-S. Lee

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