We explore the chaotic dynamics of mass-deformed Aharony-Bergman-Jafferis-Maldacena model. To do so, we first perform a dimensional reduction this model from $2+1$ to $0+1$ dimensions, considering that fields are spatially uniform. Working in 't Hooft limit and tracing over ansatz configurations involving fuzzy 2-spheres, which described terms Gomis-Rodriguez-Gomez-Van Raamsdonk-Verlinde matric...

This paper presents a model for power load forecasting using support vector machine and chaotic time series. The new model can make more accurate prediction. In the past few years, along with power system privatization and deregulation, accurate forecast of electricity load has received increasing attention. According to the chaotic and non-linear characters of power load data, the model of sup...

In this paper, we study the establishment of AC electric arc furnace model via chaotic circuit. First, the static model based on energy conservation theory is established. Then, a dynamic model based on static model created previous is built to simulate AC electric arc furnace dynamic characteristics. Chua’s chaotic circuit is selected to generate modulation wave. The results obtained by using ...

In this paper, we introduce a new method to implement chaotic generators based on Henon map chaotic system given by the state equations by using Filed Programmable Gate Array (FPGA). The aim of this method is to increase the frequency of the chaotic generators. The new method is based on MATLAB Software, Xilinx System Generator, Xilinx Alliance tools, Leonardo spectrum or Synplicity Synplify an...

The accurate traffic flow time series prediction is the prerequisite for achieving traffic flow inducible system. Aiming at the issue about multi-step prediction traffic flow chaotic time series, the traffic flow Volterra Neural Network (VNN) rapid learning algorithm is proposed. Combing with the chaos theory and the Volterra functional analysis, method of the truncation order and the truncatio...

This paper proposes a chaotic time series model of server systemwide energy consumption to capture the dynamics present in observed sensor readings of underlying physical systems. Based on the chaotic model, we have developed a real-time predictor that estimates actual server energy consumption according to its overall thermal envelope. This chaotic time series regression model relates processo...

Various forms of chaotic synchronization have been proposed as ways of implementing associative memories and/or pattern recognizers. Within this context, a single chaotic dynamical system can be adopted as an implicit model of a whole class of approximately periodic signals [De Feo, 2003]. Then, by exploiting the selective properties of the recently illustrated phenomenon of Qualitative Resonan...