电线电缆标准中数值修约规则的应用研究

对于电线电缆标准的评定,通常有两种方法,即全数值比较法和数值修约比较法,其中数值修约比较法使用范围更加广泛,它主要包括四舍五入数值修约法和GB/T8170数值修约规则两种。本文将对这两种修约法进行简要阐述,并就此进行方法和结果的比较,希望能为选择何种方法进行电线电缆标准评定提供一点帮助,并希望能够进一步对这两种修约法予以规范。     

数值修约规则在电线电缆标准中的应用与比较

电线电缆标准及试验方法标准的多项性能要求,通过试验测定和数据计算,有全数值比较法与数值修约(roundingoffnumericalfor values)比较法两种评定方法。其中,常用的数值修约方法有四舍五入数值修约法以及GB/T 8170数值修约规则两种。本文所探讨的就是该两种数值修约法,并对两种修约方法和结果进行比较,旨在初步分析使用何种方法相对合理以及加强规范数值修约规则。     

对变压器冲击合闸时的励磁涌流及削弱方法的探讨

合空载电力变压器时会产生数值相当大的励磁涌流,易造成变压器差动保护装置的误动作.针对这一问题,介绍了两种削弱励磁涌流的方法:控制三相合闸时间或在变压器低压侧加装电容器.理论分析和实践均证明这两种方法是行之有效的,但利用控制三相合闸时间来削弱励磁涌流在实际应用中更具有潜力.     

中国商业银行效率的DEA和DFA对照研究——以14家商业银行1998～2002年数据为例

随着我国银行业的发展,商业银行效率日益成为人们关注的焦点.本文运用DEA法和DFA法对我国14家商业银行的效率进行了测度,并对这两种测度结果进行了对照研究,研究结果表明这两种方法测算出的商业银行效率在数值上存在显著差异,但它们在排序上具有较好的一致性.     

中国商业银行效率的DEA和DFA对照研究——以14家商业银行1998-2002年数据为例

随着我国银行业的发展，商业银行效率日益成为人们关注的焦点。本文运用DEA法和DFA法对我国14家商业银行的效率进行了测度，并对这两种测度结果进行了对照研究，研究结果表明这两种方法测算出的商业银行效率在数值上存在显著差异，但它们在排序上具有较好的一致性。     

热管耦合冻土路基的数值传热算法对比分析研究

为预测冻土路基安装热管后路基温度场的变化情况,对热管耦合冻土路基问题开展数值传热研究是一种比纯实验方法更经济可行的方法。根据是否考虑热管内部热阻及建立的热管耦合冻土路基相变传热模型,热管耦合冻土路基的数值传热算法可基本分为两类。针对这两类基本算法进行了对比分析。结果表明：通过忽略热管内部热阻,利用耦合边界处的等价第三类边界条件及根据实际地温气温条件建立的相变传热模型来研究热管耦合冻土路基问题在工程上更为可行。     

MATLAB在小电流系统单相接地故障选线中的应用

简单地叙述了MATLAB软件的发展历史以及在电力系统仿真中的应用,用简练的语句介绍了在电力系统仿真中经常使用的Simulink中的元器件及其所属的元件库。在此基础上,本文以小电流系统为分析对象,分别对中性点不接地与中性点经消弧线圈接地两种不同的系统发生单相接地短路故障后的选线问题进行了分析,并介绍了两种选线方法——零序电流比幅法和突变量检测法。对于这两种选线方法,本文采用了先进行原理分析再加以仿真应用的方法,详细的予以了介绍。通过搭建10KV电压等级的系统平台,以MATLAB为主要的仿真工具,验证了两种选线方法的可行性与正确性。除此之外,MATLAB在电力系统仿真中的种种优势以及其强大的数值分析及图形处理功能也得到了好的体现。     

用数值解方法确定分子结构的选议

本文针对分子结构确定的计算方法问题,介绍了两种常用的数值解方法。分别指出了不同方法的适用范围,结果表明,量子力学方法更适用于小分子,而Monte-Calro方法则更适用于确定大分子的链状结构。     

三维Euler方程的有限差分方法

本文用有限差分方法求解三维方Euler方程,通过构造两种成分格式讨论不同初值对数值解及解的误差,利用Matlab程序做出数值解和解误差图像。     

论普赖斯指数增长模型参数的估计--兼与刘莉同志商榷

刘莉同志在<情报理论与实践>1997年第1期上,撰文<再谈普赖斯指数规律中参数b的求法--与朱宁等商榷>(以下简称为"刘文"),该文认为朱宁同志给出的计算b的方法[1]存在问题,故提出了计算参数b的两种新方法.由于这两种方法都依赖于N0(注:N0为初始时刻的文献累积量,即1979年以前出版的图书种数的累计值),而刘文给出的N0的计算方法及其数值45 722[2]是错误的,因此刘文给出的这两种方法都是不正确的.本文将对刘文中出现的问题作出分析,在此基础上提出改进方法.     

Application of numerical inverse Laplace transform algorithms in fractional calculus

Laplace transform technique has been considered as an efficient way in solving differential equations with integer-order. But for differential equations with non-integer order, the Laplace transform technique works effectively only for relatively simple equations, because of the difficulties of calculating inversion of Laplace transforms. Motivated by finding an easy way to numerically solve the complicated fractional-order differential equations, we investigate the validity of applying numerical inverse Laplace transform algorithms in fractional calculus. Three numerical inverse Laplace transform algorithms, named Invlap, Gavsteh and NILT, were tested using Laplace transforms of fractional-order equations. Based on the comparison between analytical results and numerical inverse Laplace transform algorithm results, the effectiveness and reliability of numerical inverse Laplace transform algorithms for fractional-order differential equations was confirmed.     

总能量守恒与辛几何算法

以正压大气原始方程为例子,以总能量守恒为主线,介绍动力保守系统两类重要算法———总能量守恒算法和辛几何算法,讨论了两者之间的关系,并给出具体的算例,说明两类算法的有效性.     

Two-stage continuous-time triggered algorithms for constrained distributed optimization over directed graphs

This paper proposes two-stage continuous-time triggered algorithms for solving distributed optimization problems with inequality constraints over directed graphs. The inequality constraints are penalized by adopting log-barrier penalty method. The first stage of the proposed algorithms is capable of finding the optimal point of each local optimization problem in finite time. In the second stage of the proposed algorithms, zero-gradient-sum algorithms with time-triggered and event-triggered communication strategies are considered in order to reduce communication costs. Then, with the help of LaSalle’s invariance principle, it is proved that the state solution of each agent reaches consensus at the optimal point of the considered penalty distributed optimization problem, and Zeno behavior is also excluded. Finally, numerical examples are given to illustrate the effectiveness of the proposed algorithms.     

New explicit iteration algorithms for solving coupled continuous Markovian jump Lyapunov matrix equations

In this paper, based on the Smith iteration (Smith, 1968), an inner-outer (IO) iteration algorithm for solving the coupled Lyapunov matrix equations (CLMEs) is presented. First, the IO iteration algorithm for solving the Sylvester matrix equation is proposed, and its convergence is analyzed in detail. Second, the IO iteration algorithm for solving the CLMEs is constructed. By utilizing the latest estimation, a current-estimation-based and two weighted IO iteration algorithms are also given for solving the CLMEs, respectively. Convergence analyses indicate that the iteration solutions generated by these algorithms always converge to the unique solutions to the CLMEs for any initial conditions. Finally, Several numerical examples are provided to show the superiority of the proposed numerical algorithms.     

A variational method for the numerical simulation of a boundary controllability problem for the linear and semilinear 1D wave equations

We pursue the numerical implementation of a boundary controllability problem for the 1D wave equation based on a recent variational approach to deal with such situations that consists in analyzing an error functional defined for feasible functions complying with appropriate initial, boundary, and final constraints. The nature of such scheme, as a minimization process for a certain error functional, leads to a natural numerical implementation by using typical descent algorithms. Our aim here is to explore the basic ingredients to set up such practical numerical approximations which allow us to address linear and semilinear equations with the same numerical scheme.     

An accurate numerical integration scheme for finite rotations using rotation vector parametrization

A numerical integration procedure for rotational motion using a rotation vector parametrization is explored from an engineering perspective by using rudimentary vector analysis. The incremental rotation vector, angular velocity and acceleration correspond to different tangent spaces of the rotation manifold at different times and have a non-vectorial character. We rewrite the equation of motion in terms of vectors lying in the same tangent space, facilitating vector space operations consistent with the underlying geometric structure. While any integration algorithm (that works within a vector space setting) may be used, we presently employ a family of explicit Runge-Kutta algorithms to solve this equation. While this work is primarily motivated out of a need for highly accurate numerical solutions of dissipative rotational systems of engineering interest, we also compare the numerical performance of the present scheme with some of the invariant preserving schemes, namely ALGO-C1, STW, LIEMID[EA] and SUBCYC-M. Numerical results show better local accuracy via the present approach vis-á-vis the preserving algorithms. It is also noted that the preserving algorithms do not simultaneously preserve all constants of motion. We incorporate adaptive time-stepping within the present scheme and this in turn enables still higher accuracy and a ‘near preservation’ of constants of motion over significantly longer intervals.     

A survey Of learning-Based control of robotic visual servoing systems

Major difficulties and challenges of modern robotics systems focus on how to give robots self-learning and self-decision-making ability. Visual servoing control strategy is an important strategy of robotic systems to perceive the environment via the vision. The vision can guide new robotic systems to complete more complicated tasks in complex working environments. This survey aims at describing the state-of-the-art learning-based algorithms, especially those algorithms that combine with model predictive control (MPC) used in visual servoing systems, and providing some pioneering and advanced references with several numerical simulations. The general modeling methods of visual servo and the influence of traditional control strategies on robotic visual servoing systems are introduced. The advantages of introducing neural-network-based algorithms and reinforcement-learning-based algorithms into the systems are discussed. Finally, according to the existing research progress and references, the future directions of robotic visual servoing systems are summarized and prospected.     

Distributed optimization problem for second-order multi-agent systems with event-triggered and time-triggered communication

This paper deals with the large category of convex optimization problems on the framework of second-order multi-agent systems, where each distinct agent is assigned with a local objective function, and the overall optimization problem is defined as minimizing the sum of all the local objective functions. To solve this problem, two distributed optimization algorithms are proposed, namely, a time-triggered algorithm and an event-triggered algorithm, to make all agents converge to the optimal solution of the optimization problem cooperatively. The main advantage of our algorithms is to remove unnecessary communications, and hence reduce communication costs and energy consumptions in real-time applications. Moreover, in the proposed algorithms, each agent uses only the position information from its neighbors. With the design of the Lyapunov function, the criteria about the controller parameters are derived to ensure the algorithms converge to the optimal solution. Finally, numerical examples are given to illustrate the effectiveness of the proposed algorithms.     

The relaxed gradient-based iterative algorithms for a class of generalized coupled Sylvester-conjugate matrix equations

In this paper, two relaxed gradient-based iterative algorithms for solving a class of generalized coupled Sylvester-conjugate matrix equations are proposed. The proposed algorithm is different from the gradient-based iterative algorithm and the modified gradient-based iterative algorithm that are recently available in the literature. With the real representation of a complex matrix as a tool, the sufficient and necessary condition for the convergence factor is determined to guarantee that the iterative solution given by the proposed algorithms converge to the exact solution for any initial matrices. Moreover, some sufficient convergence conditions for the suggested algorithms are presented. Finally, numerical example is provided to illustrate the effectiveness of the proposed algorithms and testify the conclusions suggested in this paper.     

Estimation fusion of nonlinear cost functions with application to multisensory Kalman filtering

This paper focuses on four fusion algorithms for the estimation of nonlinear cost function (NCF) in a multisensory environment. In multisensory filtering and control problems, NCF represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target systems for automatic control. To estimate the NCF using multisensory information, we propose one centralized and three decentralized estimation fusion algorithms. For multivariate polynomial NCFs, we propose a simple closed-form computation procedure. For general NCFs, the most popular procedure for the evaluation of their estimates is based on the unscented transformation. The effectiveness and estimation accuracy of the proposed fusion algorithms are demonstrated with theoretical and numerical examples.