Nature is characterized by its chaotic behavior. Mathematics is considered one of the appropriate tools to achieve the best definition of possible its chaos variables and process. Classical mathematics deals with the numbers as static and meaningless, but chaos mathematics deals with it as dynamic evolutionary, and value- added. This paper attempts to introduce the transportation problem re...

The study of epidemiological systems has generated deep interest in exploring the dynamical complexity common infectious diseases driven by seasonally varying contact rates. Mathematical modeling and field observations have shown that, under seasonal variation, incidence rates some endemic fluctuate dramatically dynamics is often characterized chaotic oscillations absence specific vaccination p...

We show that the so-called chaos bound, proposed by Maldacena, Shenker & Stanford, can be violated in f(T) teleparallel gravity. In particular, it is possible to select a new gravitational Lyapunov parameter, controlling chaotization of circular trajectories, black hole photo-sphere, exceed Stanford thermal bound. This feature alters standard quasi-normal modes and ringdown phase after merging ...

‎In the following text for arbitrary $X$ with at least two elements‎, ‎nonempty countable set $Gamma$‎ ‎we make a comparative study on the collection of generalized shift dynamical systems like $(X^Gamma,sigma_varphi)$ where $varphi:GammatoGamma$ is an arbitrary self-map‎. ‎We pay attention to sub-systems and combinations of generalized shifts with counterexamples regarding Devaney‎, ‎exact Dev...

In this paper, a novel and unified control approach that combines intelligent fuzzy logic methodology with impulsive control is developed for controlling a class of chaotic systems. We first introduce impulses into each subsystem of T-S fuzzy IF-THEN rules and then present a unified T-S impulsive fuzzy model for chaos control. Based on the new model, a simple and unified set of conditions for c...

Anyone who visits a large factory is likely to be astonished by the astonishing chaos of machines, products, components and workers, not to mention computers, bar codes, light signals, warehouses and recycling sites. Even with knowledge of what final products are being manufactured, and even with the help of a good guide, the apparent chaos can be disconcerting, specially if one is interested i...

We describe in this paper the application of soft computing techniques to controlling non-linear dynamical systems in real-world problems. Soft computing consists of fuzzy logic, neural networks , evolutionary computation, and chaos theory. Controlling real-world non-linear dynamical systems may require the use of several soft computing techniques to achieve the desired performance in practice....

Road traffic volumes in intercity roads are generally estimated by probability functions, statistical techniques or meta-heuristic approaches such as artificial neural networks. As the road traffic volumes depend on input variables and mainly road geometrical design, weather conditions, day or night time, weekend or national holidays and so on, these are also estimated by pattern recognition te...

In order to achieve chaotic signal processing, a dedicated chaos processor is required. The chaos processor is composed of two parts: chaos signal generation and chaos signal retrieval (Fig. 1). Chaos signal generation is used to generate chaos signal, while chaos signal retrieval is used to retrieve initial state of received chaos signal. Since chaos signal is analog in nature, with convention...

This work presents two simple and robust techniques based on time delay estimation for the respective control and synchronization of chaos systems. First, one of these techniques is applied to the control of a chaotic Lorenz system with both matched and mis-matched uncertainties. The nonlinearities in the Lorenz system is cancelled by time delay estimation and desired error dynamics is inserted...