基于群决策的多Agent资源管理模型

在大部分系统中,资源都是有限供给的.因此,为了提高系统的性能,保证资源使用的效率与公平,必须对资源进行有效的管理.而合理分配资源和解决资源使用冲突是系统资源管理的核心问题.基于群决策方法提出了一个多Agent资源管理模型,以动态优先级的方式灵活地解决了系统资源分配与使用冲突问题.     

Controllability of heterogeneous multi-agent systems under directed and weighted topology

This paper considers the controllability problem for both continuous- and discrete-time linear heterogeneous multi-agent systems with directed and weighted communication topology. First, two kinds of neighbour-based control protocols based on the distributed protocol of first-order and second-order multi-agent systems are proposed, under which it is shown that a heterogeneous multi-agent system is controllable if the underlying communication topology is controllable. Then, under special leader selection, the result shows that the controllability of a heterogeneous multi-agent system is solely decided by its communication topology graph. Furthermore, some necessary and/or sufficient conditions are derived for controllability of communication topology from algebraic and graphical perspectives. Finally, simulation examples are presented to demonstrate the effectiveness of the theoretical results.     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).     

Modeling of the hot metal silicon content in blast furnace using support vector machine optimized by an improved particle swarm optimizer

As a highly complex multi-input and multi-output system, blast furnace plays an important role in industrial development. Although much research has been done in the past few decades, there still exist many problems to be solved, such as the modeling problem. This paper adopts support vector regression (SVR) to construct the prediction model of blast furnace silicon content. To ensure a good generalization performance for the given datasets, it is important to select proper parameters for SVR. In view of this problem, a new particle swarm optimizer called DMS-PSO-CLS is presented to optimize the parameters of SVR. In DMS-PSO-CLS, a new cooperative learning strategy is hybridized with DMS-PSO, which makes particle information be used more effectively for generating better-quality solutions. DMS-PSO-CLS takes merits of the DMS-PSO and the cooperative learning strategy so that both the convergence speed and the convergence precision can be improved. Experimental results show that DMS-PSO-CLS can find the optimal parameters of SVR with high speed and the SVR model optimized by DMS-PSO-CLS can achieve a good regression precision on the predictive problem of blast furnace.     

On the tag localization of web video

Nowadays, numerous social videos have pervaded on the web. Social web videos are characterized with the accompanying rich contextual information which describe the content of videos and thus greatly facilitate video search and browsing. Generally, those contextual data such as tags are provided at the whole video level, without temporal indication of when they actually appear in the video, let alone the spatial annotation of object related tags in the video frames. However, many tags only describe parts of the video content. Therefore, tag localization, the process of assigning tags to the underlying relevant video segments or frames even regions in frames is gaining increasing research interests and a benchmark dataset for the fair evaluation of tag localization algorithms is highly desirable. In this paper, we describe and release a dataset called DUT-WEBV, which contains about 4,000 videos collected from YouTube portal by issuing 50 concepts as queries. These concepts cover a wide range of semantic aspects including scenes like “mountain”, events like “flood”, objects like “cows”, sites like “gas station”, and activities like “handshaking”, offering great challenges to the tag (i.e., concept) localization task. For each video of a tag, we carefully annotate the time durations when the tag appears in the video and also label the spatial location of object with mask in frames for object related tag. Besides the video itself, the contextual information, such as thumbnail images, titles, and YouTube categories, is also provided. Together with this benchmark dataset, we present a baseline for tag localization using multiple instance learning approach. Finally, we discuss some open research issues for tag localization in web videos.     

Joint design of clustering and in-cluster data route for heterogeneous wireless sensor networks

A heterogeneous wireless sensor network comprises a number of inexpensive energy constrained wireless sensor nodes which collect data from the sensing environment and transmit them toward the improved cluster head in a coordinated way. Employing clustering techniques in such networks can achieve balanced energy consumption of member nodes and prolong the network lifetimes. In classical clustering techniques, clustering and in-cluster data routes are usually separated into independent operations. Although separate considerations of these two issues simplify the system design, it is often the non-optimal lifetime expectancy for wireless sensor networks. This paper proposes an integral framework that integrates these two correlated items in an interactive entirety. For that, we develop the clustering problems using nonlinear programming. Evolution process of clustering is provided in simulations. Results show that our joint-design proposal reaches the near optimal match between member nodes and cluster heads.     

Distributed Adaptive Event‐Triggered Control for Leader‐Following Consensus of Multi‐Agent Systems

This paper studies the leader‐following consensus problem for Lipschitz nonlinear multi‐agent systems using novel event‐triggered controllers. A distributed adaptive law is introduced for the event‐based control strategy design such that the proposed controllers are independent of system parameters and only use the relative states of neighboring agents, and hence are fully distributed. Due to the introduction of an event‐triggered control scheme, the controller of the agent is only triggered at it's own event times, and thus reduces the amount of communication between controller and actuator and lowers the frequency of controller updates in practice. Based on a quadratic Lyapunov function, the event condition which uses only neighbor information and local computation at trigger instants is established. Infinite triggers within a finite time are also verified to be impossible. The effectiveness of the theoretical results are illustrated through simulation examples.     

Flocking of multi‐agent nonholonomic systems with unknown leader dynamics and relative measurements

In this paper, we consider the distributed flocking control problem of multi‐agent nonholonomic systems with a virtual leader whose dynamics is unknown; state information is time varying and not available to all agents under both fixed and switching topologies. On the basis of the relative velocity and orientation information of neighboring agents, two distributed discontinuous control protocols are designed for fixed and switching topologies, respectively. By using tools from algebraic graph theory and nonsmooth analysis, the proposed distributed discontinuous control protocols guarantee that the velocities and orientations of the agents exponentially converge to the velocity and orientation of the virtual leader, respectively, while ensuring collision avoidance of the whole group, if the interaction graph among agents is undirected and the virtual leader with bounded time‐varying velocity has directed paths to other agents. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.     

基于点对匹配的印刷电路板CT图像配准方法

针对PCB CT图像在拼接时存在较多相似区域无法有效配准的问题,提出一种基于点对匹配的方法.首先根据邻近特征点生成特征点对,并简化一种快速低维的特征描述子KPB-SIFT来描述特征点对,然后通过规定点对方向和点对分类匹配降低误匹配,最后给出一种匹配点方向约束条件,并基于该条件提出一种错误匹配点抑制算法提取正确匹配点.实验结果表明,该算法在保持较低时间复杂度的同时,匹配正确率达到95.58％,能够提取较多均匀分布的正确匹配点,从而能有效地解决PCB CT图像的配准问题.     

共享存储器交换机的性能分析

交换机是分组网中的一个重要组成部分,对于分组网的性能有着很大影响。介绍共享存储器交换机的三种不同实现方法以及多播的实现过程．同时以排队论的知识为理论分析基础,介绍排队论中的生灭过程模型,状态转移模型和爱尔兰呼损模型,并对状态转移的稳态特性以及共享存储器结构的交换机的丢包率公式给出推导。对所做的工作做简要的总结,并指明未来的研究重点．