What is it about?
Complex systems are naturally pervasive and man-made systems, and because CN could be regarded as the bedrock of complex systems they appear in a wide range of scenarios stretching from societal and environmental to biological and technological systems. Stimulated by experimental and pragmatic analysis of interacted or connected systems such as the Internet, biological, and social networks, This paper presents in particular, the outsets of degree distributions, the small-world effect, network correlations, clustering, synchronization, random graph models, models of network growth and special attachment, robustness and dynamical processes- interestingly taking place on networks.
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Why is it important?
It aims at serving as a substratum for future research in the study area, particularly those pursuing their career synthetically in artificial intelligence. In the end, some important conclusions and possible research directions of CN that essentially need to be studied in the future are proposed.
Perspectives
As human beings, we are bounded by complex networks hence need to apprehend the complexities involved and how they work. I would recommend this paper to any researcher seeking to carry out a further research in the subject area especially new researchers in the field
Dr. Ben-Bright Benuwa
Data Link Institute
Read the Original
This page is a summary of: Review of Complex Networks, International Journal of Computer Applications, May 2016, Foundation of Computer Science,
DOI: 10.5120/ijca2016909624.
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