预测状态表示(Predictive State Representations,PSRs)是用于解决局部可观测问题的有效方法.然而,现实环境中,通过样本学习得到的PSR模型不可能完全准确.随着计算步数的增多,利用PSR模型计算得到的预测向量有可能越来越偏离其真实值,...预测状态表示(Predictive State Representations,PSRs)是用于解决局部可观测问题的有效方法.然而,现实环境中,通过样本学习得到的PSR模型不可能完全准确.随着计算步数的增多,利用PSR模型计算得到的预测向量有可能越来越偏离其真实值,进而导致PSR模型的预测精度越来越低.文中提出了一种PSR模型的复位算法.通过使用判别分析方法确定系统所处的PSR状态,文中所提算法可对利用计算获取的预测向量复位,从而提高PSR模型的准确性.实验结果表明,采用复位算法的PSR模型在预测精度上明显优于未采用复位算法的PSR模型,验证了所提算法的有效性.展开更多
By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) for...By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects.展开更多
Within the OECD/NEA Benchmarking of Thermal-Hydraulic Loop Models for Lead-Alloy Cooled Advanced Nuclear Energy Systems （LACANES）, the Institute for Neutron Physics and Reactor Technology takes part in the validatio...Within the OECD/NEA Benchmarking of Thermal-Hydraulic Loop Models for Lead-Alloy Cooled Advanced Nuclear Energy Systems （LACANES）, the Institute for Neutron Physics and Reactor Technology takes part in the validation process of system codes and the characterization of the thermal-hydraulic behavior of an experimental loop operated with liquid lead-bismuth-eutectics. To confirm the calculations, the results were compared to experimental data obtained from the HELIOS facility at the Seoul National University and to the results of other benchmark participants. The comparison showed that the calculations are within measurement tolerance but nevertheless discrepancies among the participants exist. The pressure drop estimation is determined by a variety of empirical correlations for the friction and the form loss coefficients. Hence, uncertainty and sensitivity measures were applied to find out which parameter is more relevant for the overall pressure drop. In the frame of this investigation, the system code TRACE and the software system for uncertainty and sensitivity, SUSA, were used. The results show that the total pressure drop varies between -30 and ＋15% related to the reference case.展开更多
文摘预测状态表示(Predictive State Representations,PSRs)是用于解决局部可观测问题的有效方法.然而,现实环境中,通过样本学习得到的PSR模型不可能完全准确.随着计算步数的增多,利用PSR模型计算得到的预测向量有可能越来越偏离其真实值,进而导致PSR模型的预测精度越来越低.文中提出了一种PSR模型的复位算法.通过使用判别分析方法确定系统所处的PSR状态,文中所提算法可对利用计算获取的预测向量复位,从而提高PSR模型的准确性.实验结果表明,采用复位算法的PSR模型在预测精度上明显优于未采用复位算法的PSR模型,验证了所提算法的有效性.
基金Project(70572090) supported by the National Natural Science Foundation of China
文摘By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects.
文摘Within the OECD/NEA Benchmarking of Thermal-Hydraulic Loop Models for Lead-Alloy Cooled Advanced Nuclear Energy Systems （LACANES）, the Institute for Neutron Physics and Reactor Technology takes part in the validation process of system codes and the characterization of the thermal-hydraulic behavior of an experimental loop operated with liquid lead-bismuth-eutectics. To confirm the calculations, the results were compared to experimental data obtained from the HELIOS facility at the Seoul National University and to the results of other benchmark participants. The comparison showed that the calculations are within measurement tolerance but nevertheless discrepancies among the participants exist. The pressure drop estimation is determined by a variety of empirical correlations for the friction and the form loss coefficients. Hence, uncertainty and sensitivity measures were applied to find out which parameter is more relevant for the overall pressure drop. In the frame of this investigation, the system code TRACE and the software system for uncertainty and sensitivity, SUSA, were used. The results show that the total pressure drop varies between -30 and ＋15% related to the reference case.
