The study of complex networks is a new powerful tool that can provide a profitable skeleton
to better elucidate technology-related phenomena and interactions between components of …

For system failure prediction, automatically modeling from historical failure dataset is one of
the challenges in practical engineering fields. In this paper, an effective algorithm is …

The failure propagation process has always been a research hotspot in the field of complex
system reliability. Most of the research studies focus on the inference of network structure …

Large scale networked systems are playing an indispensable role in modern society, and
thus the robustness of these systems against random failures or malicious attacks has …

Assessing network systems for failures is critical to mitigate the risk and develop proactive
responses. In this paper, we investigate devastating consequences of link failures in …

Nowadays people are becoming increasingly dependent on networks. Taking precautions
before failure of networks is becoming more and more important. Compared with detection …

Bayesian Network (BN) is a graphical network model for the description of the variables
between causal uncertainties. It is built for uncertainty modeling and reasoning, processing …

In this paper, we study the use of the chaining strategy introduced by Jordan and Graves
(1995) for designing a robust production/supply chain network in which the links and nodes …

As an important research direction of complex networks and data mining, link prediction has
attracted more and more scholars' attention. In the early research, the common neighbor is …

Cascading failures in complex networks have attracted widespread attention in recent years.
In this paper, a cascade model is proposed to analyze the potential overloads of nodes and …