突发事件快速评估模型

突发事件发生初期,进行突发事件的快速综合评估,有利于及时、准确地把握事件的态势,以满足应急决策的时效性要求.为解决突发事件数据量较大,数据更新较快时,过于复杂的运算过程和计算软件缺乏以及已有软件兼容性低而难以满足应急决策的时效性要求的问题,本文简化了Simos过程和PROMETHEEⅡ方法,构建了突发事件快速评估模型,即SSPPM(Simple Simos'Procedure and PROMETHEEⅡModel).为了验证新模型的有效性,本文选取了两个数据进行实验.实验结果表明,在对评估速度的要求大于对精度的要求的突发事件控制阶段,新模型能快速综合多位应急决策者的意见,快速获取权重,简化评估过程,提高突发事件综合评估效率.     

电力二次系统安全防护综合仿真试验床研究

分析比较了现有的信息与网络安全仿真模型,指出各自模型的适用性和局限性.在以往主要针对局部对象进行安全仿真的研究基础上,结合电力二次系统整体安全防护需求,综合运用8种仿真技术和方案,设计实现了基于4个仿真层次,17个种类仿真试验的信息安全综合仿真试验床,实现针对电力信息系统的大型、分布式、联动式的综合信息安全仿真.使用证明,试验床能够为电力信息系统安全防护工程设计和实施提供多方位的仿真测试和评估依据.     

Learning multivariate time series causal graphs based on conditional mutual information

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis.This paper provides a method that employs both mutual information and conditional mutual information to identify the causal structure of multivariate time series causal graphical models.A three-step procedure is developed to learn the contemporaneous and the lagged causal relationships of time series causal graphs.Contrary to conventional constraint-based algorithm, the proposed algorithm does not involve any special kinds of distribution and is nonparametric.These properties are especially appealing for inference of time series causal graphs when the prior knowledge about the data model is not available.Simulations and case analysis demonstrate the effectiveness of the method.     

LEARNING CAUSAL GRAPHS OF NONLINEAR STRUCTURAL VECTOR AUTOREGRESSIVE MODEL USING INFORMATION THEORY CRITERIA

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis. Traditional causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. Although additive model regression can effectively infer the nonlinear causal relationships of additive nonlinear time series, it suffers from the limitation that contemporaneous causal relationships of variables must be linear and not always valid to test conditional independence relations. This paper provides a nonparametric method that employs both mutual information and conditional mutual information to identify causal structure of a class of nonlinear time series models, which extends the additive nonlinear times series to nonlinear structural vector autoregressive models. An algorithm is developed to learn the contemporaneous and the lagged causal relationships of variables. Simulations demonstrate the effectiveness of the nroosed method.     

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

Some classical penalty function algorithms may not always be convergent under big penalty parameters in Matlab software, which makes them impossible to find out an optimal solution to constrained optimization problems. In this paper, a novel penalty function (called M-objective penalty function) with one penalty parameter added to both objective and constrained functions of inequality constrained optimization problems is proposed. Based on the M-objective penalty function, an algorithm is developed to solve an optimal solution to the inequality constrained optimization problems, with its convergence proved under some conditions. Furthermore, numerical results show that the proposed algorithm has a much better convergence than the classical penalty function algorithms under big penalty parameters, and is efficient in choosing a penalty parameter in a large range in Matlab software.     

加工能力受扰的可控排序干扰管理

在加工时间可控的单机排序中,面对随机发生的干扰事件,研究了初始加工时间表的制定问题。对于干扰事件造成的影响采用匹配时间排序的应对策略,在干扰事件发生后,通过压缩工件加工时间,使新时间表在某时间点后完全恢复到初始加工时间表。基于工件吸收干扰事件影响的能力,设计复合排序规则来决定工件的优先级。由于问题内在的复杂性,在复合排序规则中,应用遗传算法来确定某给定待处理工件集的最优参数。使用概率分布表示干扰事件的发生时刻和持续时间,并综合概率信息和工件的优先级来制定初始加工时间表。最后,通过随机数值试验模拟,发现本文设计的初始时间表优于根据最短加工时间优先规则制定的初始时间表,验证了方法对于处理干扰事件影响的有效性。     

Secure and efficient elliptic curve cryptography resists side-channel attacks

An embedded cryptosystem needs higher reconfiguration capability and security. After analyzing the newly emerging side-channel attacks on elliptic curve cryptosystem (ECC), an efficient fractional width-w NAF (FWNAF) algorithm is proposed to secure ECC scalar multiplication from these attacks. This algorithm adopts the fractional window method and probabilistic SPA scheme to recondigure the pre-computed table, and it allows designers to make a dynamic configuration on pre-computed table. And then, it is enhanced to resist SPA, DPA, RPA and ZPA attacks by using the random masking method. Compared with the WBRIP and EBRIP methods, our proposals has the lowest total computation cost and reduce the shake phenomenon due to sharp fluctuation on computation performance.     

Novel passive localization algorithm based on weighted restricted total least square

A novel multi-observer passive localization algorithm based on the weighted restricted total least square (WRTLS) is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound (CRLB), and the localization solution is asymptotically unbiased.     

两种算术函数上下界的讨论

在自然数中，任意自然数ｎ都可由若干个１通过加、减、乘法运算表示出来；也可以去掉减号，由若干个１通过加和乘法表示出来。在ｎ的所有可能的表示法中，我们分别用ｆ（ｎ）和ｇ（ｎ）记这两种表示法中包含１的个数最少的那种表示法中所含１的个数，参考文献［１］中给出了ｆ（ｎ）的一个较强的上下界估计，本文进一步证明了不等式３ｌｏｇ３ｎ≤ｆ（ｎ）≤３．６８ｌｏｇ３ｎ３ｌｏｇ３ｎ≤ｇ（ｎ）≤４．７６ｌｏｇ３ｎ并讨论了∑ｎ≤ｘｆ（ｎ），∑ｎ≤ｘｇ（ｎ），的渐近性质     

邮电信息系统体系结构研究

通过分析邮电信息系统的建设现状，结合邮电企业的具体情况，提出了邮电信息系统体系结构的建立原则、内容及一种邮电信息系统建设框架模型，以实现对邮电信息系统建设的全面规划、综合考虑系统功能的设定与结构的设计。