衡量网络可靠性的新模型

本文分析了传统的网络可靠性优化设计方法所存在的问题 ,给出了网络的通信通路数的定义 ,并基于网络的通信通路数给出了更能反映网络运行的实际情况的网络可靠性的定量模型 ,从而解决了传统网络可靠性优化设计方法所存在的问题 .     

AFS结构分解算法及其在复杂系统故障诊断中的应用

通过复杂系统上AFS结构的分析，进一步研究了复杂系统上AFS结构如何分解为若干个相互独立的子AFS结构，给出了AFS结构直和分解算法。在对复杂系统进行分析和故障诊断时，这种算法有效地降低了系统的复杂程度，从而减少了系统的故障判断和处理的难度，并应用Matlab给出了一种船用柴油机的系统分析和故障诊断的应用实例。     

基于无线传感器网络的可靠性模型及上界

无线传感器网络的技术应用与开发对网络的性能要求越来越高.从保证网络可靠性和服务质量角度考虑无线传感器网络性能参数.给出了保障服务质量的网络可靠性数学模型,由于可靠性计算是NP难问题,进一步研究该网络模型的可靠性上界.通过利用点割集代替极小割的方法提出了可靠性上界的计算公式.仿真结果表明,上界结果对评估网络可靠性精确值的近似效果较好.     

一种针对代谢网络多平衡态性质的强连通分解方法

针对反应速率满足一定条件的代谢网络,提出了一种强连通分解方法对网络进行分解,通过研究分解后的子网络来分析整体网络的多平衡态性质.基于代谢网络的拓扑结构,构造了其对应的代谢反应图和相互作用图,引入了紧缩运算的定义,构造了强连通分解算法;给出了该算法的计算复杂度,证明了分解的唯一性以及分解后子网络的强连通性,阐明了子网络与整体网络在多平衡态性质意义下的关系,举例说明了强连通算法和所得主要结果的有效性.     

基于动态Bayes网络的结构时变可靠性分析

针对存在抗力退化结构的时变可靠性问题,提出一种动态贝叶斯网络(dynamic Bayesian network,DBN)模型,以gamma过程作为抗力退化模型,并离散为Bayes网络,同时建立观测模型、可靠性模型,组合为动态Bayes网络,通过连续节点消除与离散得到仅含离散变量的动态Bayes网络;给出精确推理的3种情况,评估现在(滤波)、未来(预测)以及过去时刻(平滑)结构的状态.当测量信息出现时,对退化模型参数重新估计,利用精确推理来更新结构时变可靠性.以存在抗力退化的一跨刚架作为研究对象,验证了模型的合理性.     

复杂客户网络稳定性分析

在客户网络中,负面客户会对企业的利益造成损失,忠诚客户和一般客户是企业利润的主要源泉.对复杂客户网络的稳定性分析能够从技术角度分析复杂网络的客户认知度对于网络稳定性的影响,从而为企业制定客户稳定性策略提供建议.从客户的平均初始认知度、客户的初始认知度在客户网络中的分布及客户网络的平均认知度对客户网络稳定性的影响等角度对复杂客户网络的稳定性进行了研究,并由此提出增强复杂客户网络稳定性的对策:提高客户的初始认知度、增加客户交流的机会和把握重点客户等.     

无线传感器网络传输可靠性计算

无线传感器网络是由传感器节点和汇聚节点组成的以数据为中心的无线网络.汇聚节点根据一个或多个源节点传送的采集数据对事件进行监测和判断,而数据传输的可靠性直接影响到监测和判断的准确性.在无线传感器网络中,一方面,网络拓扑结构是动态变化的,数据传输的可靠性与网络拓扑结构有关;另一方面,网络中的传感器节点是能最受限的,因此传输的可靠性还与节点的能昔密切相关-针对无线传感器网络的特点,给出了无线传感器网络的传输可靠性概念,提出一种传输可靠性度量,分别在有数据融合和无数据融合两种情况下,对网络节点的能耗情况进行了分析,获得r网络节点正常工作的概率随时间的变化关系,并导出数学表达式,用于计算节点所产生的数据包成功传输给汇聚节点的概率,从而获得了求整个网络传输可靠性的计算方法.     

循环债务问题的数学模型和优化算法

给出了循环债务问题的一种非常直观的数学模型，通过将债务网络分解为双向连通分支，依次寻求并破除各分支的最大容量有向圈，为实施企业间的债务对消，解决循环债务问题提供了一种切实可行的方法－分解破圈法。     

基于云模型和PageRank算法的社会网络群决策方法

近年来，随着信息、通信和技术的快速发展，决策者之间的关系也由此变得越来越紧密。在此背景下，决策者基于社会网络关系存在交互，社会网络群体决策会产生比传统群体决策更多的信息，信息不完全性、随机性以及决策者有限理性等因素都会导致群体决策结果与实际情况产生偏差。针对社会网络群体决策中决策偏好信息为定性概念的语言信息，且决策者之间存在信任度的群体决策问题，本文提出了一种基于云模型和PageRank算法的社会网络群决策方法并针对现有的云聚类算法拓展出了社会网络云聚类算法。首先，将语言信息转化为云模型；其次，基于社会网络拓扑图利用PageRank算法来计算每个决策者的权重；接着，使用社会网络云聚类算法将决策者分成几个子聚集并求出子聚集的权重；最后把云模型综合成方案云，利用随机模拟技术获取各个方案云的评分，给出方案的排序，并通过对比分析验证了该方法的有效性。     

分解定理的网络结构分析

本文首先将逻辑神经元推广为模糊逻辑神经元，在此基础上证明了有关分解定理建模的两个重要定理，最后给出了分解定理的网络表示。     

A cross entropy approach to design of reliable networks

One of the most important parameters determining the performance of communication networks is network reliability. The network reliability strongly depends on not only topological layout of the communication networks but also reliability and availability of the communication facilities. The selection of optimal network topology is an NP-hard problem so that computation time of enumeration-based methods grows exponentially with network size. This paper presents a new solution approach based on cross-entropy method, called NCE, to design of communication networks. The design problem is to find a network topology with minimum cost such that all-terminal reliability is not less than a given level of reliability. To investigate the effectiveness of the proposed NCE, comparisons with other heuristic approaches given in the literature for the design problem are carried out in a three-stage experimental study. Computational results show that NCE is an effective heuristic approach to design of reliable networks.     

Stochastic multi-scale finite element based reliability analysis for laminated composite structures

This paper proposes a novel multi-scale approach for the reliability analysis of composite structures that accounts for both microscopic and macroscopic uncertainties, such as constituent material properties and ply angle. The stochastic structural responses, which establish the relationship between structural responses and random variables, are achieved using a stochastic multi-scale finite element method, which integrates computational homogenisation with the stochastic finite element method. This is further combined with the first- and second-order reliability methods to create a unique reliability analysis framework. To assess this approach, the deterministic computational homogenisation method is combined with the Monte Carlo method as an alternative reliability method. Numerical examples are used to demonstrate the capability of the proposed method in measuring the safety of composite structures. The paper shows that it provides estimates very close to those from Monte Carlo method, but is significantly more efficient in terms of computational time. It is advocated that this new method can be a fundamental element in the development of stochastic multi-scale design methods for composite structures.     

The Cross-Entropy Method for Network Reliability Estimation

Consider a network of unreliable links, modelling for example a communication network. Estimating the reliability of the network—expressed as the probability that certain nodes in the network are connected—is a computationally difficult task. In this paper we study how the Cross-Entropy method can be used to obtain more efficient network reliability estimation procedures. Three techniques of estimation are considered: Crude Monte Carlo and the more sophisticated Permutation Monte Carlo and Merge Process. We show that the Cross-Entropy method yields a speed-up over all three techniques.     

Specialized study to perform complex phase synchronization of two chaotic complex systems including a similar structure of direct terms with modifying in nonlinear terms

We ponder a different kind of complex synchronization. We name this sort “complex phase synchronization” (CPHS). This review concentrates on two chaotic complex structures, including a similar structure of direct terms with totally differing or incompletely in nonlinear terms. A novel plan is needed to complete the complex phase synchronization (CPHS) for the chaotic complex structures. In this plan, we have utilized the dependability hypothesis to decide diagnostically the complex control capacities that are expected to accomplish CPHS. From this plan, we found that CPHS holds or incorporates two sorts of synchronizations (phase and anti-phase synchronizations) and the state factors of the main structure synchronize with alternate state factors of the slave structure. We connected this plan, for instance, to study the CPHS of two chaotic complex Lü structures with incompletely changing in nonlinear terms. These complex (or mind-boggling) structures resemble in various imperative areas of mineral science and building. Numerical outcomes are sketched out to uncover the phases and modules errors of these chaotic attractors, subsequently communicating that CPHS is fulfilled. A specific application in secure communication is designed. Amongst this secure communication, CPHS between transmitter and collector is the key to the information signs are regained.     

A simple algorithm to search for all MCs in networks

Evaluating the network reliability is an important topic in the planning, designing, and control of systems. The minimal cut (MC, an edge set) set is one of the major and fundamental tools for evaluating the network reliability. In this study, an alternative method is given to define a MC using a node set (called MCV). A very simple algorithm based on some intuitive theorems that characterize the structure of the MCV and the relationship between MC and MCV is developed to find the MCs between two special nodes. The proposed algorithm is then generalized to find all MCs between all pairs of nodes. The proposed algorithm is not only easier to understand and implement, but is also better than the existing best-known algorithm. The correctness of the proposed algorithm will be analyzed and proven. One example is illustrated to show how all MCs are generated and verified in a network using the proposed algorithm.     

考虑n中连续取k失效准则的树状系统可靠性求解方法

树状网络系统在管道运输,网络通信中较为常见,对其进行可靠性评估对系统设计及优化具有重要意义。针对树状冗余系统,在n中连续取k失效准则下,通过有限马尔可夫嵌入法并对其进行变形,研究了树状系统可靠性求解方法。本文对树状系统建模加以定义,提出了基于层数参数,层-节点向量,父-子节点矩阵三元参数的树状系统表示方法,研究了变形有限马尔可夫嵌入法的树状系统n中连续取k失效准则下的可靠性求解方法,给出了三个数值算例应用并分析了算法的运算复杂度。最后,本文对比讨论了基于概率母函数法的树状系统在n中连续取k准则下系统可靠性求解方法的研究,得出结论本文算法针对树状冗余系统n中连续取k失效准则下系统可靠性求解应用范围更广,求解效率较高。     

大型网络基于连通可靠度的最优可靠度分配

由于网络连通可靠度计算属于NP-hard问题,当系统可靠度无法显式表达时,基于连通可靠度的大型复杂网络优化通常只能采用启发式优化算法解决．通过对复杂网络连通可靠度算法结构的分析,给出了系统连通可靠度的Taylor方程．采用遗传算法,由系统连通可靠度的Taylor方程确定种群适应值,得到一个系统最优可靠度分配方案;将最优解带入改进Minty算法或递推分解算法中,计算该最优解的连通可靠度精确值和对应的连通可靠度的Taylor展开方程;再次采用遗传算法求最优解．当最优解对应的可靠度精确值和Taylor方程算得得近似值误差小于指定精度时,则此最优解为最终的系统最优可靠度分配方案A·D2将此优化过程称为迭代遗传算法．算例显示迭代遗传算法不仅可用于大型网络的连通可靠度最优分配,而且优化迭代过程中可以得到多组阶段最优解,这些解均落在最优解附近,构成了近似最优解群,在实际工程优化中拓展了选择面．     

Decomposition of network communication games

Using network control structures, this paper introduces a general class of network communication games and studies their decomposition into unanimity games. We obtain a relation between the dividends in any network communication game and its underlying transferable utility game, which depends on the structure of the communication network. Moreover, we introduce a new class of network control values which contains both the Myerson value and the position value. The decomposition results are used to explicitly express these values in terms of dividends.     

基于韧性度的低轨卫星通信网络抗毁性度量及优化

低轨卫星通信网络的抗毁性是描述网络安全可靠的有效工具,在网络体系结构设计和路由策略等领域得到了广泛的应用。根据低轨卫星通信网络中卫星在轨道平面内移动,需要不断进行切换的特点,从建立抗毁性测度模型以及网络抗毁性优化两个角度来评估和提高网络抗毁性,提出一种基于韧性度的低轨卫星通信网络抗毁性度量方法。通过对移动模型以及切换模型的结构分析,对每种结构以一定概率出现的低轨卫星通信网络,应用韧性度函数,求得网络在某个时刻及某一段时间段内的抗毁性,并针对切换模型的不足之处进行优化,用赋权韧性度来体现优化的效果,得到了优化后的网络抗毁性。以铱星系统为应用实例进行仿真,结果表明:任意时刻网络的抗毁性跟拓扑结构的韧性度值有关,并且是一种线性关系,即随着韧性度的增加,其抗毁性也增加。通过对铱星通信系统切换模型的优化,网络的抗毁性与平均抗毁性都得到了提升,说明本文所构建模型的有效性和实用性。     

A longitudinal study of evolving networks in response to natural disaster

In this study, we present a longitudinal analysis of the evolution of interorganizational disaster coordination networks (IoDCNs) in response to natural disasters. There are very few systematic empirical studies which try to quantify the optimal functioning of emerging networks dealing with natural disasters. We suggest that social network analysis is a useful method for exploring this complex phenomenon from both theoretical and methodological perspective aiming to develop a quantitative assessment framework which could aid in developing a better understanding of the optimal functioning of these emerging IoDCN during natural disasters. This analysis highlights the importance of utilizing network metrics to investigate disaster response coordination networks. Results of our investigation suggest that in disasters the rate of communication increases and creates the conditions where organizational structures need to move at that same pace to exchange new information. Our analysis also shows that inter-organizational coordination network structures are not fixed and vary in each period during a disaster depending on the needs. This may serve the basis for developing preparedness among agencies with an improved perspective for gaining effectiveness and efficiency in responding to natural disasters.