n-Dimensional Chaotic Time Series Prediction Method

Liu, Fang; Yin, Baohui; Cheng, Mowen; Feng, Yongxin

doi:10.3390/electronics12010160

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…By constantly pumping or releasing energy in the system, the system can be stabilized in a chaotic state. According to the literature [26], the Hamiltonian of equation (3) is as follows (6):…”

Section: Hamiltonianmentioning

confidence: 99%

“…Chaos refers to seemingly random irregular motion [5] occurring in a deterministic system, which is an inherent characteristic of nonlinear dynamic systems. The system is described by deterministic differential equations, but it is characterized by uncertainty, nonrepeatability and unpredictability [6,7]. The Lorenz chaotic system, due to its complex dynamic behavior and strange attractive substructure [8], has drawn great attention from experts in many fields, such as atmospheric science, physics and information science [9,10].…”

Section: Introductionmentioning

confidence: 99%

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Chaotic model and control of an atmospheric convective system coupled with large-scale circulation

Zhang,

Liu,

et al. 2024

Phys. Scr.

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Large-scale weather systems affect or determine the generation, development and movement of small- and medium-scale convective weather systems, and the understanding of their influence mechanism is of great significance for the prediction and forecasting of small- and medium-scale convective systems. From the perspective of dynamics, based on the Lorenz–Stenflo model describing convective systems and the Lorenz84 model describing low-order atmospheric circulation, we construct a chaotic model of an atmospheric convective system considering large-scale circulation, analyze the influence of the system parameters on the convective system, and design a state feedback controller to adjust the convective motion. For the constructed convective weather system model, the existence and boundedness of its solution are analyzed, the Hamiltonian quantity is solved, the dynamic characteristics of the Lyapunov index, bifurcation diagram, attractor phase diagram and other methods are used to analyze its dynamic characteristics, the physical significance of its dynamic behavior is discussed, and the influence mechanism of the system parameters on convective weather is given. Additionally, the temperature difference between the upper and lower air currents is changed by the state feedback method, which provides a feasible scheme for adjusting the intensity of convective motion. The simulation experiments show that the chaotic model can explain and reveal the complex dynamic behavior of large-scale weather circulation in small- and medium-scale convective systems, which is of great significance for improving the prediction accuracy of convective systems in local areas, and feedback control can obtain the desired convective motion state.

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Section: Hamiltonianmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Chaotic model and control of an atmospheric convective system coupled with large-scale circulation

Zhang,

Liu,

et al. 2024

Phys. Scr.

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“…Inventory shows strong chaotic characteristics with time; that is, inventory is neither periodic nor random [1]. Chaotic behavior makes forecasting more difficult, leading to new tools development, to investigate whether the time series data are chaotic [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Dynamics and Complexity Analysis of Fractional-Order Inventory Management System Model

Lei,

Li,

Deeprasert

et al. 2024

Fractal Fract

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To accurately depict inventory management over time, this paper introduces a fractional inventory management model that builds upon the existing classical inventory management framework. According to the definition of fractional difference equation, the numerical solution and phase diagram of an inventory management system are obtained by MATLAB simulation. The influence of parameters on the nonlinear behavior of the system is analyzed by a bifurcation diagram and largest Lyapunov exponent (LLE). Combined with the related indexes of time series, the complex characteristics of a quantization system are analyzed using spectral entropy and C0. This study concluded that the changing law of system complexity is consistent with the LLE of the system. By analyzing the influence of order on the system, it is found that the inventory changes will be periodic in some areas when the system is fractional, which is close to the actual conditions of the company’s inventory situation. The research results of this paper provide useful information for inventory managers to implement inventory and facility management strategies.

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Design and FPGA implementation of a high-speed PRNG based on an n-D non-degenerate chaotic system

Luo,

Fan,

et al. 2024

Chaos, Solitons & Fractals

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n-Dimensional Chaotic Time Series Prediction Method

Cited by 3 publications

References 24 publications

Chaotic model and control of an atmospheric convective system coupled with large-scale circulation

Chaotic model and control of an atmospheric convective system coupled with large-scale circulation

Dynamics and Complexity Analysis of Fractional-Order Inventory Management System Model

Design and FPGA implementation of a high-speed PRNG based on an n-D non-degenerate chaotic system

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