Different delays-induced regime shifts in a stochastic insect outbreak dynamics

Zeng, Jiakui; Zeng, Chunhua; Xie, Qingshuang; Guan, Lin; Dong, Xiaohui; Yang, Fang

doi:10.1016/j.physa.2016.06.115

Cited by 47 publications

(7 citation statements)

References 64 publications

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“…The equation (12) is used to define the response amplitude gain Q ( ω 3 ) of ω 3 output by the system at the low frequency signal, which is used to study the degree of vibration resonance. 22,23…”

Section: Vibration Resonance Analysis Of Two-stage Braided Gear Systemmentioning

confidence: 99%

Response analysis of 3D braided two-stage gear system excited by different frequency signals

Zhang

Tang

et al. 2021

Advances in Mechanical Engineering

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The knitting principle of 3D braided gear was studied, and the dynamic model of the two-stage gear system was established. The fourth-order Runge-Kutta method was used to numerically simulate the dynamic characteristics of common gear and 3D braided gear. The results showed that the fundamental frequency ω1 of the static transmission error excitation had the greatest effect on the speed and frequency characteristics of the first-stage gear along the meshing line. The research on frequency characteristics of common gear and 3D braided gear shows that the fundamental frequency ω1 of the static transmission error excitation has a large effect on the speed and frequency characteristics of the first-stage gear along the meshing line. With the reduction of the gear mass and moment of inertia, the amplitude in the low-frequency band increases. The vibration resonance of the system is studied by defining the amplitude gain of the response of the system output at the low-frequency signal ω3. The results show that with the reduction of gear mass and moment of inertia, when the input stage torque fluctuation frequency is Ω > 5, the fluctuation of amplitude gain Q disappears, which indicates that the vibration resistance of the 3D braided gear to high-frequency input stage torque fluctuation frequency is greatly improved.

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Section: Vibration Resonance Analysis Of Two-stage Braided Gear Systemmentioning

confidence: 99%

Response analysis of 3D braided two-stage gear system excited by different frequency signals

Zhang

Tang

et al. 2021

Advances in Mechanical Engineering

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“…One calculates the cross-correlation coefficients between the output series for different delays and finds the specific delay at which the absolute value of the cross-correlation coefficient reaches the maximum, called time delay for the cross-correlation. [15] The value of the cross-correlation and the time delay stability are used cooperatively to identify the influence. The Granger causality [16] of one market, for another example, implies that the history of the causal market has a significant ability to explain the present state of the explained market, which is evaluated by regressions of the structural equations.…”

Section: Introductionmentioning

confidence: 99%

Information flow between stock markets: A Koopman decomposition approach

Semba¹,

Huiyun²,

Gu³

et al. 2022

Chinese Phys. B

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Stock markets in the world are linked by complicated and dynamical relationships into a temporal network. Extensive works have provided us with rich findings from the topological properties and their evolutionary trajectories, but the underlying dynamical mechanism is still not in order. In the present work, we proposed a technical scheme to reveal the dynamical law from the temporal network. The index records for the global stock markets form a multivariate time series. One separates the series into segments and calculates the information flows between the markets, resulting in a temporal market network representing the state and its evolution. Then the technique of the Koopman decomposition operator is adopted to find the law stored in the information flows. The results show that the stock market system has a high flexibility, i.e., it jumps easily between different states. The information flows mainly from high to low volatility stock markets. And the dynamical process of information flow is composed of many dynamic modes distribute homogenously in a wide range of periods from one month to several ten years, but there exist only nine modes dominating the macroscopic patterns.

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“…The effects of time delay on stochastic system have been investigated by many researchers [12][13][14][15]. More recently, the influences of time delay in stochastic insect outbreak model has been investigated [16]. They reported that the multiplicative noise, positive cross-correlation between additive and multiplicative noise, time delays can induce the regime shifts.…”

Section: Introductionmentioning

confidence: 99%

Delay induced dynamical behaviors in a stochastic insect outbreak model in presence of Michaelis-Menten type harvesting

Mandal¹,

Poria

2021

Phys. Scr.

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In this paper, we have considered stochastic insect outbreak model in presence of Michaelis-Menten type of harvesting. The growth of the insect species is taken as delayed logistic type together with a multiplicative noise term. The impact of internal environmental disturbances on the insect population is taken into account by adding an additive noise term in the model. The effects of the noises, cross correlation strength of the noises and time delay on the insect population are investigated and observed very rich dynamical behaviors. It is ascertained that multiplicative noise reduces population size greatly than additive noise. As usual, increase of harvesting of insect species reduces the population size at faster rate. Regime shift is possible depending on multiplicative noise only in contrast it is not possible via only additive noise. One of the key finding is the noise-delayed switching phenomenon for negatively correlated noises.

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Different delays-induced regime shifts in a stochastic insect outbreak dynamics

Cited by 47 publications

References 64 publications

Response analysis of 3D braided two-stage gear system excited by different frequency signals

Response analysis of 3D braided two-stage gear system excited by different frequency signals

Information flow between stock markets: A Koopman decomposition approach

Delay induced dynamical behaviors in a stochastic insect outbreak model in presence of Michaelis-Menten type harvesting

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