The permanence of a nonlinear higher order discrete time system from macroeconomics is studied, and a sufficient condition is proposed for the permanence of the system described by 11(,...,)nnnnkxrxfxx---=+ where :kfR...The permanence of a nonlinear higher order discrete time system from macroeconomics is studied, and a sufficient condition is proposed for the permanence of the system described by 11(,...,)nnnnkxrxfxx---=+ where :kfRR, the initial values 01,,kxx-are real numbers and [0,1)r is constant after exploring the relationship between this equation and 1(,...,)nnnkxfxx--= for certain classes of function f. As an application a short proof is given to a known result in a simpler way than ever reported.展开更多
The author considers a three-species ratio-dependent predator-prey model with time delay in a two-patch environments. This model is of periodic coefficients, which incorporates the periodicity of the environment. By m...The author considers a three-species ratio-dependent predator-prey model with time delay in a two-patch environments. This model is of periodic coefficients, which incorporates the periodicity of the environment. By means of the coincidence degree theory, sufficient conditions for the existence of at least one positive periodic solution of this model are established. Moreover, The author shows that the system is uniformly persistent under the conditions.展开更多
Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!....Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.展开更多
基金the Technology Research Foundation of the State Ministry of Education (No. 02130)
文摘The permanence of a nonlinear higher order discrete time system from macroeconomics is studied, and a sufficient condition is proposed for the permanence of the system described by 11(,...,)nnnnkxrxfxx---=+ where :kfRR, the initial values 01,,kxx-are real numbers and [0,1)r is constant after exploring the relationship between this equation and 1(,...,)nnnkxfxx--= for certain classes of function f. As an application a short proof is given to a known result in a simpler way than ever reported.
基金The research is supported by the Scientific Research Foundation of the Doctor Department of Hubei University of Technology.
文摘The author considers a three-species ratio-dependent predator-prey model with time delay in a two-patch environments. This model is of periodic coefficients, which incorporates the periodicity of the environment. By means of the coincidence degree theory, sufficient conditions for the existence of at least one positive periodic solution of this model are established. Moreover, The author shows that the system is uniformly persistent under the conditions.
基金supported by the National Natural Science Foundation of China(Grant No.51377027)the National Basic Research Program of China("973"Project)(Grant No.2012CB215104)ABB(China)Ltd
文摘Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.
