A general method of constructing proxy blind signature is proposed based on multilinear transform. Based on this method, the four proxy blind signature schemes are correspondently generated with four different signatu...A general method of constructing proxy blind signature is proposed based on multilinear transform. Based on this method, the four proxy blind signature schemes are correspondently generated with four different signature equations, and each of them has four forms of variations of signs. Hence there are sixteen signatures in all, and all of them are proxy stronglyblind signature schemes. Furthermore, the two degenerated situations of multi-linear transform are discussed. Their corresponding proxy blind signature schemes are shown, too. But some schemes come from one of these degenerate situations are proxy weakly-blind signature scheme.The security for proposed scheme is analyzed in details. The results indicate that these signature schemes have many good properties such as unforgeability, distinguish-ability of proxy signature,non-repudiation and extensive value of application etc.展开更多
Efficient energy management and grid stability strongly rely on accurate Short-Term Load Forecasting(STLF).Existing forecasting models,unfortunately,are often inaccurate and computationally demanding.To overcome these...Efficient energy management and grid stability strongly rely on accurate Short-Term Load Forecasting(STLF).Existing forecasting models,unfortunately,are often inaccurate and computationally demanding.To overcome these challenges,a novel hybrid model,combining both linear regression and machine learning techniques,is proposed in this study.The hybrid model,MLR-LSTM-FFNN,captures both temporal and non-linear de-pendencies in load data by integrating multi-linear regression(MLR)with long short-term memory(LSTM)networks and feed-forward neural networks(FFNN).Using datasets from Qatar,with 5 min,15 min,30 min,and 1 h time intervals and from Panama City with a 1 h interval,experiments were conducted to thoroughly test the robustness of the model.The results showed that the MLR-LSTM-FFNN hybrid model outperformed the baseline and state-of-the-art hybrid models for each of the datasets,in terms of lower RMSE,MAE,and MAPE values along with a faster training time.This superior performance across different datasets underscores the model’s scal-ability and reliability as an STLF approach,providing a practical solution to energy demand prediction tasks.The improvement in short-term forecasting accuracy provides utilities with a practical tool to optimize demand-side management,reduce operational costs,and enhance grid reliability.展开更多
该文提出一种考虑故障后多阶段恢复的智能软开关(soft open point,SOP)柔性互联配电网(flexible interconnected distribution network,FIDN)可靠性评估方法,其特征在于将基于SOP的FIDN网络拓扑状态通过优化过程的决策变量显式表达,建...该文提出一种考虑故障后多阶段恢复的智能软开关(soft open point,SOP)柔性互联配电网(flexible interconnected distribution network,FIDN)可靠性评估方法,其特征在于将基于SOP的FIDN网络拓扑状态通过优化过程的决策变量显式表达,建立面向FIDN可靠性评估的混合整数线性规划模型,从而实现FIDN可靠性评估。首先,分析FIDN多阶段恢复过程,提出一种多阶段恢复过程解耦建模的FIDN可靠性评估框架;然后,基于SOP正常运行和不同故障下的外特性,建立面向可靠性评估的SOP等效模型,构建FIDN节点-支路状态关联模型以实现网络拓扑状态显式化;之后,考虑SOP转供功率约束及短时过载能力,建立不同策略下的SOP快速转供模型;在此基础上,考虑SOP快速转供、故障点上游恢复、联络开关切换转供、孤岛运行等多阶段恢复过程,建立面向FIDN可靠性评估的混合整数线性规划模型;最后,在改进的37节点系统上验证所提方法的有效性。展开更多
摆振会降低起落架的使用寿命,影响乘坐舒适性,甚至会引起机体损坏,导致飞机失事。为了抑制起落架摆振,本文采用时滞反馈非线性能量汇(nonlinear energy sink,NES)对起落架摆振进行多目标优化。以某轻型飞机起落架为研究对象,设计了基于...摆振会降低起落架的使用寿命,影响乘坐舒适性,甚至会引起机体损坏,导致飞机失事。为了抑制起落架摆振,本文采用时滞反馈非线性能量汇(nonlinear energy sink,NES)对起落架摆振进行多目标优化。以某轻型飞机起落架为研究对象,设计了基于NES的时滞反馈半主动控制减摆器,并建立了前起落架摆振系统分析动力学方程。通过线性多步法求解出时滞反馈半主动控制摆振系统的特征根,分析了减摆器可控阻尼系数对特征根最大实部的影响。以时滞量为设计变量,将振幅衰减时间和第四周期振幅的线性加权组合确定为目标函数。采用粒子群算法对该优化目标进行全局搜索,得到相应的最优时滞量,并与遗传算法得到的结果进行对比,验证了最优时滞量的可靠性,并在时域内对减摆器的减摆效果进行了验证。结果表明,与无时滞控制系统相比,采用最优时滞反馈的半主动控制系统的前起落架摆振幅值显著降低。展开更多
基金Supported by the Fundamental Research Program of Commission of Science Technology and Industry for National Defence (No.J1300D004)
文摘A general method of constructing proxy blind signature is proposed based on multilinear transform. Based on this method, the four proxy blind signature schemes are correspondently generated with four different signature equations, and each of them has four forms of variations of signs. Hence there are sixteen signatures in all, and all of them are proxy stronglyblind signature schemes. Furthermore, the two degenerated situations of multi-linear transform are discussed. Their corresponding proxy blind signature schemes are shown, too. But some schemes come from one of these degenerate situations are proxy weakly-blind signature scheme.The security for proposed scheme is analyzed in details. The results indicate that these signature schemes have many good properties such as unforgeability, distinguish-ability of proxy signature,non-repudiation and extensive value of application etc.
基金support from the Qatar National Research Fund through grant AICC05-0508-230001(Solar Trade(ST):An Equitable and Efficient Blockchain-Enabled Renewable Energy Ecosystem-“Oppor-tunities for Fintech to Scale up Green Finance for Clean Energy”)and from Qatar Environment and Energy Research Institute is gratefully acknowledged.
文摘Efficient energy management and grid stability strongly rely on accurate Short-Term Load Forecasting(STLF).Existing forecasting models,unfortunately,are often inaccurate and computationally demanding.To overcome these challenges,a novel hybrid model,combining both linear regression and machine learning techniques,is proposed in this study.The hybrid model,MLR-LSTM-FFNN,captures both temporal and non-linear de-pendencies in load data by integrating multi-linear regression(MLR)with long short-term memory(LSTM)networks and feed-forward neural networks(FFNN).Using datasets from Qatar,with 5 min,15 min,30 min,and 1 h time intervals and from Panama City with a 1 h interval,experiments were conducted to thoroughly test the robustness of the model.The results showed that the MLR-LSTM-FFNN hybrid model outperformed the baseline and state-of-the-art hybrid models for each of the datasets,in terms of lower RMSE,MAE,and MAPE values along with a faster training time.This superior performance across different datasets underscores the model’s scal-ability and reliability as an STLF approach,providing a practical solution to energy demand prediction tasks.The improvement in short-term forecasting accuracy provides utilities with a practical tool to optimize demand-side management,reduce operational costs,and enhance grid reliability.
文摘该文提出一种考虑故障后多阶段恢复的智能软开关(soft open point,SOP)柔性互联配电网(flexible interconnected distribution network,FIDN)可靠性评估方法,其特征在于将基于SOP的FIDN网络拓扑状态通过优化过程的决策变量显式表达,建立面向FIDN可靠性评估的混合整数线性规划模型,从而实现FIDN可靠性评估。首先,分析FIDN多阶段恢复过程,提出一种多阶段恢复过程解耦建模的FIDN可靠性评估框架;然后,基于SOP正常运行和不同故障下的外特性,建立面向可靠性评估的SOP等效模型,构建FIDN节点-支路状态关联模型以实现网络拓扑状态显式化;之后,考虑SOP转供功率约束及短时过载能力,建立不同策略下的SOP快速转供模型;在此基础上,考虑SOP快速转供、故障点上游恢复、联络开关切换转供、孤岛运行等多阶段恢复过程,建立面向FIDN可靠性评估的混合整数线性规划模型;最后,在改进的37节点系统上验证所提方法的有效性。
文摘摆振会降低起落架的使用寿命,影响乘坐舒适性,甚至会引起机体损坏,导致飞机失事。为了抑制起落架摆振,本文采用时滞反馈非线性能量汇(nonlinear energy sink,NES)对起落架摆振进行多目标优化。以某轻型飞机起落架为研究对象,设计了基于NES的时滞反馈半主动控制减摆器,并建立了前起落架摆振系统分析动力学方程。通过线性多步法求解出时滞反馈半主动控制摆振系统的特征根,分析了减摆器可控阻尼系数对特征根最大实部的影响。以时滞量为设计变量,将振幅衰减时间和第四周期振幅的线性加权组合确定为目标函数。采用粒子群算法对该优化目标进行全局搜索,得到相应的最优时滞量,并与遗传算法得到的结果进行对比,验证了最优时滞量的可靠性,并在时域内对减摆器的减摆效果进行了验证。结果表明,与无时滞控制系统相比,采用最优时滞反馈的半主动控制系统的前起落架摆振幅值显著降低。
