基于节点支路链矩阵的配电网动态拓扑分析方法研究与应用*

针对配电网中现有拓扑分析方法运算复杂、速度较慢、重用性较差,以及当配网规模扩大或开关状态改变时,不易及时地反映网络拓扑信息等问题,提出基于支路链矩阵的配电网动态拓扑分析方法。在系统正常运行时,采用特殊节点法将配电网划分多个支路链子图,以节点-支路链矩阵描述配网拓扑结构,借助邻接矩阵标记法与深度优先搜索原则结合完成更新后的拓扑网络的电气岛连通性分析。当支路动态变化时,根据支路属性利用方向深度优先搜索法快速地修改网络拓扑结构,局部更新节点-支路链矩阵。多个实例结果表明该方法可适应多种配电网接线结构,搜索过程中节点数量明显减少,降低了算法复杂度,提高了拓扑分析速度,为不同配网结构动态分析提供了一种有效的方法。     

赫夫曼树遍历算法的优化

对数据结构中赫夫曼树和赫夫曼遍历的算法问题进行探讨,针对传统使用的遍历算法存在循环次数较多、算法时间复杂度较大问题,通过修改参数和循环体结构对原有算法进行改进,从而减少循环次数,降低算法时间复杂度,同时也提出了动态编码算法等的优点和可行性。     

信息系统体系结构复杂性度量方法研究*

体系结构技术是进行信息系统设计的重要技术,其复杂性直接决定着建设信息系统的复杂性。研究了程序复杂性的度量方法,在复杂性概念研究的基础上,提出了将体系结构复杂性分为动态复杂性和结构复杂性分开进行度量的方法,并提出基于熵的动态复杂性和结构复杂性评估方法。通过对体系结构复杂性度量方法的研究,可以有效地度量体系结构的复杂性,为项目开发与决策提供有力的依据。     

赫夫曼树遍历算法的优化

对数据结构中赫夫曼树和赫夫曼遍历的算法问题进行探讨,针对传统使用的遍历算法存在循环次数较多、算法时间复杂度较大问题,通过修改参数和循环体结构对原有算法进行改进,从而减少循环次数,降低算法时间复杂度,同时也提出了动态编码算法等的优点和可行性。     

基于四叉堆优先级队列及逆邻接表的改进型Dijkstra算法

在深入分析传统Ｄｉｊｋｓｔｒａ算法的基础上,提出了利用基于ｋ叉堆的优先级队列对算法进行改进的思想,并对３种可合并替进行了比较,从理论上证明了四叉堆在ｋ叉堆中的最优性,设计了基于四叉堆优先级队列及逆领接表,顾及路段方向阻抗的改进型Ｄｉｊｋｓｔｒａ最短径算法,将Ｄｉｊｓｔｒａ算法复杂度降为Ｏ（ｎｌｏｇｎ）。     

On 0′-computable reals

Given a 0′-computable real x we are interested in the relative complexity of the sets A_z = {i: z_i < x} for possible computable sequences of rationals z = {z_s} with lim_sz_s = x, with respect to a strong reducibility ≤ = _r. It turns out that the r-degree structure of these sets (excluding the trivial, i.e. the finite and co-finite ones) is a substructure of the ≤ = _r-degrees inside the Turing degree of x and it can be non-trivial. In fact, we construct a real x = lim_sz_s = lim_sw_s such that A_zwttA_w. Also, it can be trivial even for non-computable reals x: there is a non-computable c.e. real x such that for all sequences z with lim_sz_s = x the sets A_z (if co-infinite) have the same m-degree. Assigning such a degree structure to each 0′-computable real we propose the study of the complexity of a single real by means of the complexity of the correspondent degree structure. The variety of these degree structures from real to real indicates that a fine classification of the 0′-computable reals may be possible in this way. Finally, we study the immunity properties of A_z: we prove that it cannot be (co-)hyperhyperimmune but it is always bi-hyperimmune or (co-)hypersimple if x is non-computable.     

基于四叉堆优先级队列及逆邻接表的改进型Dijkstra 算法

在深入分析传统Ｄｉｊｋｓｔｒａ算法的基础上,提出了利用基于ｋ 叉堆的优先级队列对算法进行改进的思想,并对３ 种可合并堆进行了比较,从理论上证明了四叉堆在ｋ 叉堆中的最优性,设计了基于四叉堆优先级队列及逆邻接表、顾及路段方向阻抗的改进型Ｄｉｊｋｓｔｒａ最短路径算法,将Ｄｉｊｋｓｔｒａ 算法复杂度降为Ｏ（ｎｌｏｇｎ）。针对ＧＩＳ－Ｔ应用系统的动态特征,提出了Ｄｉｊｋｓｔｒａ 算法的逆序计算方法,通过构造逆序最短路径树,使算法更具灵活性和实用性     

一种基于资源约束的Agent组织规则生成机制

Agent组织是多Agent系统的一种求解结构，可以有效地降低求解难度和Agent之间的交互复杂性，对Agent组织的抽象包括组织结构，组织规则和组织模式，Agent组织规则的形成是Agent组织设计的重要问题之一，基于资源约束给出了Agent组织规则的形式描述和产生机制，设计了Agent组织规则形成的静态算法和动态算法，从而改进了Zambonelli和Jennings关于Agent组织规则的研究。     

基于UML的概念模型的Petri网映射算法研究

概念模型的动态部分由于其复杂性不易通过阅读式的审查实施验证,针对采用统一建模语言(UML)描述的概念模型,通过UML时序图模型向Petri网模型的映射,可建立Petri网可执行模型,再对其进行验证.在深入分析UML时序图特点的基础上,针对已有映射方法存在的缺点,提出了基于消息的模型映射算法,并对时序图中的特殊结构(可选、条件、并行、循环),分别提出了其相应的映射算法,并验证了映射的正确性.方法有利于检查模型映射前后的一致性,同时具有可扩展的优点.     

A review of supply chain complexity drivers

Studies on supply chain complexity mainly use the static and dynamic complexity distinction. While static complexity describes the structure of the supply chain, the number and the variety of its components and strengths of interactions between these; the dynamic complexity represents the uncertainty in the supply chain and involves the aspects of time and randomness. This distinction is also valid when classifying the drivers of supply chain complexity according to the way they are generated. Supply chain complexity drivers (e.g., number/variety of suppliers, number/variety of customers, number/variety of interactions, conflicting policies, demand amplification, differing/conflicting/non-synchronized decisions and actions, incompatible IT systems) play a significant and varying role in dealing with complexity of the different types of supply chains (e.g., food, chemical, electronics, automotive).     

The twisted crossed cube

The topology of interconnection networks plays an important role in the performance of parallel and distributed computing systems. In this paper, we propose a new interconnection network called twisted crossed cube (TCQ_n) and investigate its basic network properties in terms of the regularity, connectivity, fault tolerance, recursiveness, hamiltonicity and ability to simulate other architectures, and so on. Then, we develop an effective routing algorithm Route (u, v) for TCQ_n that takes no more than d(u, v) + 1 steps for any two nodes (u, v) to communicate with each other, and the routing process shows that the diameter, wide diameter, and fault‐tolerant diameter of TCQ_n are about half of the corresponding diameters of the equivalent hypercube with the same dimension. In the end, by combining TCQ_n with crossed cube (CQ_n), we propose a preferable dynamic network structure, that is, the dynamic crossed cube, which has the same network diameter as TCQ_n/CQ_n and better properties in other respects, for example, its connection complexity is half of that of TCQ_n/CQ_n when the network scale is large enough, and the number of its average routing steps is also much smaller than that in TCQ_n/CQ_n. Copyright © 2015 John Wiley & Sons, Ltd.     

A robust adaptive dynamic surface control for a class of nonlinear systems with unknown Prandtl–Ishilinskii hysteresis

In this paper, a robust adaptive dynamic surface control for a class of uncertain perturbed strict‐feedback nonlinear systems preceded by unknown Prandtl–Ishlinskii hysteresis is proposed. The main advantages of our scheme are that the explosion of complexity problem can be eliminated when the hysteresis is fused with backstepping design and, by introducing an initialization technique, the ??_∞ performance of system tracking error can be achieved. It is proved that the new scheme can guarantee semi‐global uniform ultimate boundedness of all closed‐loop signals and make the convergence of the tracking error to an arbitrarily small residual set. Simulation results are presented to demonstrate the efficiency of the proposed scheme. Copyright © 2010 John Wiley & Sons, Ltd.     

A low‐complexity design for distributed containment control of networked pure‐feedback systems and its application to fault‐tolerant control

This paper addresses a low‐complexity distributed containment control problem and its extension to fault‐tolerant control for networked nonlinear pure‐feedback systems under a directed graph. The multiple dynamic leaders are neighbors of only a subset of the followers described by completely non‐affine multi‐input multi‐output pure‐feedback dynamics. It is assumed that all followers' nonlinearities are heterogeneous and unknown. The proposed containment controller is implemented by using only error surfaces integrated by performance bounding functions and does not require any differential equations for compensating uncertainties and faults. Thus, compared with the previous containment control approaches for multi‐agent systems with unknown non‐affine nonlinearities, the distributed containment control structure is simplified. In addition, it is shown that the proposed control scheme can be applied to the fault‐tolerant containment control problem in the presence of unexpected system and actuator faults, without reconstructing any control structure. It is shown from Lyapunov stability theorem that all followers nearly converge to the dynamic convex hull spanned by the dynamic leaders and the containment control errors are preserved within certain given predefined bounds. Copyright © 2016 John Wiley & Sons, Ltd.     

Structural effects of R&D collaboration network on knowledge diffusion performance

With the advent of knowledge-based economy, the process and structure of knowledge diffusion mechanism in R&D collaboration networks have become more complex and dynamic. However, regardless of the complexity and importance of these R&D collaboration networks, previous empirical analyses have focused mainly on statics, which cannot be a sufficient basis to thoroughly explore knowledge diffusion in the R&D collaboration network. Furthermore, there has been little research done on the relationship between knowledge diffusion and the structure of an R&D collaboration network. Hence, this paper modeled knowledge diffusion based on social network analysis. It also investigated the impact of network structure on the performance of knowledge diffusion, focusing on average knowledge stock and knowledge variance. The results confirm that the small-world network is the most efficient and equitable structure toward effective knowledge diffusion.     

Dynamic interval index structure in constraint database systems

Interval index structure plays an important role in constraint database systems.A dynamic interval index structure DM-tree is presented in this paper.The advantage of the DM-tree compared with other interval index structures is that the dynamic operations of insertion and deletion can be operated on the new structure.The storage complexity of the tree is O(n),and the query I/O complexity is O(longn t/B).To improve the performance of the inserting and deleting operations some methods such as neighbored-constraint and update-late are applied.The I/O complexity of inserting and deleting operations is the same as that in B-tree.i.e.,.O(logn).     

Multivariable adaptive dynamic surface control based on norm estimation of unknown parameter matrices

In this article, a novel output-feedback adaptive dynamic surface control scheme is proposed for linear time-invariant multivariable plants based on the norm estimation of unknown parameter matrices. Besides avoiding the explosion of complexity problem in traditional multivariable backstepping design, the proposed scheme has the following features: (1) only one parameter needs to be updated on-line regardless of the plant order and input–output dimension, (2) only the Hurwitz condition is required for the high-frequency gain matrix and (3) the ?_∞ performance of the tracking error can be guaranteed. It is shown that all signals of the closed-loop system are semi-globally uniformly bounded. Simulation results are given to illustrate the effectiveness of the proposed scheme.     

The generalized momentum approach to the dynamic modeling of a 6-dof parallel manipulator

Dynamic modeling is of great importance regarding computer simulation and advanced control of parallel manipulators. Due to their closed-loop structure and kinematic constraints, dynamic modeling of parallel manipulators presents an inherent complexity. Despite the intensive investigation in this topic of robotics, mostly conducted in the last 2 decades, additional research still has to be done in this area. The dynamic model of a parallel manipulator is usually developed using the Newton–Euler or the Lagrange methods. Nevertheless, additional approaches were also investigated, such as the virtual work, and screw theory based approaches. In this paper, an approach based on the manipulator generalized momentum is studied. This approach is used to obtain the dynamic model of a six degrees-of-freedom parallel manipulator. The involved computational effort is evaluated and compared with the one involved within the classic Lagrange’s formulation. It is showed the proposed approach presents a much lower computational burden.     

A robust output-feedback adaptive dynamic surface control for linear systems with input disturbance

In this paper, a robust output-feedback adaptive control is proposed for linear time-invariant (LTI) singleinput single-output (SISO) plants with unmeasurable input disturbance. Using dynamic surface control (DSC) technique, it is shown that the explosion of complexity problem in backstepping control can be eliminated. Furthermore, the proposed adaptive DSC scheme has the following merits: 1) by introducing an initialization technique, the L∞ performance of system tracking error can be guaranteed even if the plant high-frequency gain is unknown and the input disturbance exists, and 2) the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. It is proved that with the proposed scheme, all the closed-loop signals are semiglobally uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.     

Dynamic Programming Revisited: Improving Knapsack Algorithms

The contribution of this paper is twofold: At first an improved dynamic programming algorithm for the bounded knapsack problem is given. It decreases the running time for an instance with n items and capacity c from to , which is the same pseudopolynomial complexity as usually given for the 0--1 knapsack problem. In the second part a general approach based on dynamic programming is presented to reduce the storage requirements for combinatorial optimization problems where it is computationally more expensive to compute the explicit solution structure than the optimal solution value. Among other applications of this scheme it is shown that the 0--1 knapsack problem as well as the bounded knapsack problem can be solved in time and space. Received: October 15, 1998; revised March 10, 1999     

A recognition network model-based approach to dynamic image understanding

In this paper, we present definitions for a dynamic knowledge-based image understanding system. From a sequence of grey level images, the system produces a flow of image interpretations. We use a semantic network to represent the knowledge embodied in the system. Dynamic representation is achieved by ahypotheses network. This network is a graph in which nodes represent information and arcs relations. A control strategy performs a continuous update of this network. The originality of our work lies in the control strategy: it includes astructure tracking phase, using the representation structure obtained from previous images to reduce the computational complexity of understanding processes. We demonstrate that in our case the computational complexity, which is exponential if we only use a purely data-driven bottom-up scheme, is polynomial when using the hypotheses tracking mechanism. This is to say that gain improvement in computation time is a major reason for dynamic understanding. The proposed system is implemented; experimental results of road mark detection and tracking are given.