We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (D...We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (DPD) model. The magnitude of WG and FD-GMM estimates are almost the same for square panels. WG estimator performs best for long panels such as those with time dimension as large as 50. The advantage of FD-GMM estimator however, is observed on panels that are long and wide, say with time dimension at least 25 and cross-section dimension size of at least 30. For small-sized panels, the two methods failed since their optimality was established in the context of asymptotic theory. We developed parametric bootstrap versions of WG and FD-GMM estimators. Simulation study indicates the advantages of the bootstrap methods under small sample cases on the assumption that variances of the individual effects and the disturbances are of similar magnitude. The boostrapped WG and FD-GMM estimators are optimal for small samples.展开更多
针对我国当前经济、政策变动的大背景,提出了采用数据分组处理方法GMDH(group method of data handling)结合多结构突变理论,实现时序突变点自动搜索建模,建立了中长期负荷预测的GMDH多结构自动搜索模型。该模型能够客观准确地搜索时间...针对我国当前经济、政策变动的大背景,提出了采用数据分组处理方法GMDH(group method of data handling)结合多结构突变理论,实现时序突变点自动搜索建模,建立了中长期负荷预测的GMDH多结构自动搜索模型。该模型能够客观准确地搜索时间序列中的所有突变点,并充分利用突变点信息修正由于经济环境和突发事件引起的预测偏差,大大提高了传统时序外推预测模型的精度。华东地区的实际算例结果表明了该模型的有效性。展开更多
This paper describes a method for energy calibration of laterally segmented electromagnetic calorimeters based on the detection of two-photon decays of π~0 mesons.The calibration procedure performs a X^2 function min...This paper describes a method for energy calibration of laterally segmented electromagnetic calorimeters based on the detection of two-photon decays of π~0 mesons.The calibration procedure performs a X^2 function minimization between the measured π~0 energy in the calorimeter and its expected energy deduced from the π~0 momentum direction. The performance of this technique is demonstrated with a Monte Carlo simulation of an experimental case where biased calibration coefficients are employed. The real calibration coefficients are restored with less than 1% relative accuracy when a sufficient number of π~0 is detected. This technique is applied to monitor daily the calibration coefficients of the calorimeter used in the Jefferson Lab Hall A DVCS experiments.展开更多
In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Mo...In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.展开更多
文摘We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (DPD) model. The magnitude of WG and FD-GMM estimates are almost the same for square panels. WG estimator performs best for long panels such as those with time dimension as large as 50. The advantage of FD-GMM estimator however, is observed on panels that are long and wide, say with time dimension at least 25 and cross-section dimension size of at least 30. For small-sized panels, the two methods failed since their optimality was established in the context of asymptotic theory. We developed parametric bootstrap versions of WG and FD-GMM estimators. Simulation study indicates the advantages of the bootstrap methods under small sample cases on the assumption that variances of the individual effects and the disturbances are of similar magnitude. The boostrapped WG and FD-GMM estimators are optimal for small samples.
文摘针对我国当前经济、政策变动的大背景,提出了采用数据分组处理方法GMDH(group method of data handling)结合多结构突变理论,实现时序突变点自动搜索建模,建立了中长期负荷预测的GMDH多结构自动搜索模型。该模型能够客观准确地搜索时间序列中的所有突变点,并充分利用突变点信息修正由于经济环境和突发事件引起的预测偏差,大大提高了传统时序外推预测模型的精度。华东地区的实际算例结果表明了该模型的有效性。
文摘This paper describes a method for energy calibration of laterally segmented electromagnetic calorimeters based on the detection of two-photon decays of π~0 mesons.The calibration procedure performs a X^2 function minimization between the measured π~0 energy in the calorimeter and its expected energy deduced from the π~0 momentum direction. The performance of this technique is demonstrated with a Monte Carlo simulation of an experimental case where biased calibration coefficients are employed. The real calibration coefficients are restored with less than 1% relative accuracy when a sufficient number of π~0 is detected. This technique is applied to monitor daily the calibration coefficients of the calorimeter used in the Jefferson Lab Hall A DVCS experiments.
文摘In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.
