Real-time traffic flow estimation is important for online traffic control and management. The traffic state estimator optimally matches traffic measurements from detectors with traffic flow predictions from a dynamic traffic model under a certain control strategy. The current and widely used...

Estimation of complexity is of great interest in nonlinear signal and system analysis. Several complexity measures have been proposed: Lyapunov exponents, Lempel and Ziv, approximate entropy. In the present study, complexity measures derived from Shannon entropy,...

The performance of analog forecasts is sensitive to the selection procedure of analogs from the history of observed time series. A method is presented to iteratively reduce a user-defined forecast error measure by adapting suitable metric weights for the components of the reconstructed states to...

Conditional independence graphs are proposed for describing the dependence structure of multivariate nonlinear time series, which extend the graphical modeling approach based on partial correlation. The vertexes represent the components of a multivariate time series and edges denote direct...

Microblog is one of the most popular communication channels on the Internet, and has already become the third largest source of news and public opinions in China. Although researchers have studied the information propagation in microblog using the epidemic models, previous studies have not...

We propose a stochastic SIR model with or without distributed time delay and we study the stability of disease-free equilibrium. The numerical simulation of the stochastic SIR model shows that the introduction of noise modifies the threshold of system for an epidemic to occur and the threshold...

With the prevalence of new media, e.g., microblogging, rumors spread faster and wider than ever before. On the basis of prior studies, this paper modifies a flow chart of the rumor spreading process with the SIR (Susceptible, Infected, and Recovered) model, and thus makes the rumor spreading...

Identifying influential nodes that lead to faster and wider spreading in complex networks is of theoretical and practical significance. The degree centrality method is very simple but of little relevance. Global metrics such as betweenness centrality and closeness centrality can better identify...

We use scale-free networks to study properties of the infected mass M of the network during a spreading process as a function of the infection probability q and the structural scaling exponent γ. We use the standard SIR model and investigate in detail the distribution of M. We find that for...

As people travel, human contact networks may change topologically from time to time. In this paper, we study the problem of epidemic spreading on this kind of dynamic network, specifically the one in which the rewiring dynamics of edges are carried out to preserve the degree of each node (called...