对非线性价格函数:P(D)=p0(1+1D),用差分方程相关理论,分别对双寡头垄断的两种对策:古诺对策和斯坦克贝对策,研究了产量对策系统的稳定性.由于非线性函数形式复杂,这里借助计算机,运用D e lph i编写程序,并引进一个新的参数λ—单位最...对非线性价格函数:P(D)=p0(1+1D),用差分方程相关理论,分别对双寡头垄断的两种对策:古诺对策和斯坦克贝对策,研究了产量对策系统的稳定性.由于非线性函数形式复杂,这里借助计算机,运用D e lph i编写程序,并引进一个新的参数λ—单位最高风险比,讨论了λ的范围、初值的范围与系统稳定性的关系,得到了在一定条件下系统大范围渐近稳定的结论.展开更多
The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers o...The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities （LMIs） approach, to minimize the upper bound of a quadratic cost fimction under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs＇ magnitudes be guaranteed. Thus, with the above muki-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.展开更多
Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroe...Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.展开更多
In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-d...In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d （independent and identically distributed） property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.展开更多
A discrete nonlinear model of real estate is derived,with which the evolutionary trendamong government,consumers and real estate developers is described.The stability,bifurcation,andchaotic behavior of the system are ...A discrete nonlinear model of real estate is derived,with which the evolutionary trendamong government,consumers and real estate developers is described.The stability,bifurcation,andchaotic behavior of the system are also analyzed by using nonlinear dynamic method.Results show thatchaos can be obtained via quasi-periodic transition and double-periodic bifurcation.The influence ofdynamic evolutionary trend among stakeholder on system stability is also studied and some interestingconclusions are derived.This research can effectively explain the complex behavior of housing prices.展开更多
By applying two nonlinear Granger causality testing methods and rolling window strategy to explore the relationship between speculative activities and crude oil prices, the unidirectional Granger causality from specul...By applying two nonlinear Granger causality testing methods and rolling window strategy to explore the relationship between speculative activities and crude oil prices, the unidirectional Granger causality from speculative activities to returns of crude oil prices during the high price phase is discovered. It is proved that speculative activities did contribute to high crude oil prices after the Asian financial crisis and OPEC＇s output cut in 1998. The unidirectional Granger causality from returns of crude oil prices to speculative activities is significant in general. But after 2000, with the sharp rise in crude oil prices, this unidirectional Granger causality became a complex nonlinear relationship, which cannot be detected by any linear Granger causaIity test.展开更多
文摘对非线性价格函数:P(D)=p0(1+1D),用差分方程相关理论,分别对双寡头垄断的两种对策:古诺对策和斯坦克贝对策,研究了产量对策系统的稳定性.由于非线性函数形式复杂,这里借助计算机,运用D e lph i编写程序,并引进一个新的参数λ—单位最高风险比,讨论了λ的范围、初值的范围与系统稳定性的关系,得到了在一定条件下系统大范围渐近稳定的结论.
基金the National Natural Science Foundation of China (No. 60574082)the National Creative Research Groups Sci-ence Foundation of China (No. 60721062)the China Postdoc-toral Science Foundation (No. 20070411178)
文摘The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities （LMIs） approach, to minimize the upper bound of a quadratic cost fimction under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs＇ magnitudes be guaranteed. Thus, with the above muki-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.
文摘Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.
文摘In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d （independent and identically distributed） property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.
基金supported by the National Natural Science Foundation of China under Grant Nos. 60641006,70872029.
文摘A discrete nonlinear model of real estate is derived,with which the evolutionary trendamong government,consumers and real estate developers is described.The stability,bifurcation,andchaotic behavior of the system are also analyzed by using nonlinear dynamic method.Results show thatchaos can be obtained via quasi-periodic transition and double-periodic bifurcation.The influence ofdynamic evolutionary trend among stakeholder on system stability is also studied and some interestingconclusions are derived.This research can effectively explain the complex behavior of housing prices.
基金supported by the National Natural Science Foundation of China
文摘By applying two nonlinear Granger causality testing methods and rolling window strategy to explore the relationship between speculative activities and crude oil prices, the unidirectional Granger causality from speculative activities to returns of crude oil prices during the high price phase is discovered. It is proved that speculative activities did contribute to high crude oil prices after the Asian financial crisis and OPEC＇s output cut in 1998. The unidirectional Granger causality from returns of crude oil prices to speculative activities is significant in general. But after 2000, with the sharp rise in crude oil prices, this unidirectional Granger causality became a complex nonlinear relationship, which cannot be detected by any linear Granger causaIity test.
