scholarly journals Parameter identification of fractional-order chaotic system with time delay via multi-selection differential evolution

2017 ◽  
Vol 5 (1) ◽  
pp. 42-48 ◽  
Author(s):  
Fucai Liu ◽  
Xiao Li ◽  
Xue Liu ◽  
Yinggan Tang
Keyword(s):  
Time Delay ◽  
Differential Evolution ◽  
Parameter Identification ◽  
Fractional Order ◽  
Chaotic System ◽  
Selection Differential ◽  
System With Time Delay

Parameter identification of commensurate fractional-order chaotic system via differential evolution

2012 ◽  
Vol 376 (4) ◽  
pp. 457-464 ◽  
Author(s):  
Yinggan Tang ◽  
Xiangyang Zhang ◽  
Changchun Hua ◽  
Lixiang Li ◽  
Yixian Yang
Keyword(s):  
Differential Evolution ◽  
Parameter Identification ◽  
Fractional Order ◽  
Chaotic System

scholarly journals A time delay dynamical model for outbreak of 2019-nCoV and the parameter identification

2020 ◽  
Vol 28 (2) ◽  
pp. 243-250 ◽  
Author(s):  
Yu Chen ◽  
Jin Cheng ◽  
Yu Jiang ◽  
Keji Liu
Keyword(s):  
Dynamical System ◽  
Time Delay ◽  
Parameter Identification ◽  
Typical Feature ◽  
The Novel ◽  
Isolation Rate ◽  
High Isolation ◽  
The Government ◽  
System With Time Delay ◽  
Official Data

AbstractIn this paper, we propose a novel dynamical system with time delay to describe the outbreak of 2019-nCoV in China. One typical feature of this epidemic is that it can spread in the latent period, which can therefore be described by time delay process in the differential equations. The accumulated numbers of classified populations are employed as variables, which is consistent with the official data and facilitates the parameter identification. The numerical methods for the prediction of the outbreak of 2019-nCoV and parameter identification are provided, and the numerical results show that the novel dynamic system can well predict the outbreak trend so far. Based on the numerical simulations, we suggest that the transmission of individuals should be greatly controlled with high isolation rate by the government.

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