Chaos is a nonlinear behavior that shows chaotic and irregular responses to internal and external stimuli in dynamic systems. This behavior usually appears in systems that are highly sensitive to initial condition. In these systems, stabilization is a highly considerable tool for eliminating aberrant behaviors. In this paper, the problem of stabilization and tracking the chaos are investigated....

Network traffic anomaly detection has become a popular research tendency, as it can detect new type attacks in real time. However, the network traffic appears as a complex dynamic system, causing by the collaboration of many network factors. Although various methods have been proposed to detect anomalies, they are mostly based on the traditional statistical physics. In these methods, all factor...

Since many real world networks are evolving over time, such as social and user-item networks, there increasing research efforts on dynamic network embedding in recent years. They learn node representations from a sequence of graphs but not only the latest network, for preserving both structural temporal information networks. Due to lack comprehensive investigation them, we give survey this pape...

A theoretical framework that supports automated construction of dynamic prime models purely from experimental time series data has been invented and developed, which can automatically generate (construct) data-driven models of any time series data in seconds. This has resulted in the formulation and formalisation of new reverse engineering and dynamic methods for automated systems modelling of ...

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonst...

The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). A representative technique of the framework is the dynamic interaction network (DIN), recently developed in the bioinformatics domain (Chan et al., 2006). DINs are capable of modelling dynamic interactions between genes and predicting their future expressions. In this paper, we adopt ...

design for a brain the origin of adaptive behavior PDF adaptive dynamic and resilient systems mobile services and systems PDF applications of complex adaptive systems PDF an introduction to genetic algorithms complex adaptive systems PDF signals and boundaries building blocks for complex adaptive systems PDF intelligent complex adaptive systems author ang yang apr-2011 PDF an introduction to fu...

The local community is a complex socio-economic system, and its ability to function for an indefinitely long period of time (viability) is not investigated sufficiently today. The purpose of the research was, using the cognitive mapping, propose to the local community management developing their own management strategies to ensure its viability. Considering the weakly structured subject area of...

In this paper, the design of dynamic neural networks with Kalman filter is proposed and applied to identify nonlinear dynamic systems. The optimal parameters of a dynamic neural network, which contains several autoregressive moving average (ARMA) sub models, weighs and biases, are obtained using the well known delta rule. Using the obtained parameters of the ARMA sub models, a new dynamic netwo...