Parameter Estimation and Topology Identification of Uncertain General Fractional-order Complex Dynamical Networks with Time Delay

Complex networks have attracted much attention from various fields of sciences and engineering in recent years. However, many complex networks have various uncertain information, such as unknown or uncertain system parameters and topological structure, which greatly affects the system dynamics. Thus, the parameter estimation and structure identification problem has theoretical and practical importance for uncertain complex dynamical networks. This paper investigates identification of unknown system parameters and network topologies in uncertain fractional-order complex network with time delays (including coupling delay and node delay). Based on the stability theorem of fractional-order differential system and the adaptive control technique, a novel and general method is proposed to address this challenge. Finally two representative examples are given to verify the effectiveness of the proposed approach. © 2014 Chinese Association of Automation.

Analytical and Experimental Study on Complex Compressed Air Pipe Network

To analyze the working characteristics of complex compressed air networks, numerical methods are widely used which are based on finite element technology or intelligent algorithms. However, the effectiveness of the numerical methods is limited. In this paper, to provide a new method to optimize the design and the air supply strategy of the complex compressed air pipe network, firstly, a novel method to analyze the topology structure of the compressed air flow in the pipe network is initially proposed. A matrix is used to describe the topology structure of the compressed air flow. Moreover, based on the analysis of the pressure loss of the pipe network, the relationship between the pressure and the flow of the compressed air is derived, and a prediction method of pressure fluctuation and air flow in a segment in a complex pipe network is proposed. Finally, to inspect the effectiveness of the method, an experiment with a complex network is designed. The pressure and the flow of airflow in the network are measured and studied. The results of the study show that, the predicted results with the proposed method have a good consistency with the experimental results, and that verifies the air flow prediction method of the complex pipe network. This research proposes a new method to analyze the compressed air network and a prediction method of pressure fluctuation and air flow in a segment, which can predicate the fluctuation of the pressure according to the flow of compressed air, and predicate the fluctuation of the flow according to the pressure in a segment of a complex pipe network.

Three-dimensional spatial structure of the macro-pores and flow simulation in anthracite coal based on X-ray μ-CT scanning data

The three-dimensional(3 D) structures of pores directly affect the CH4 flow.Therefore,it is very important to analyze the3 D spatial structure of pores and to simulate the CH4 flow with the connected pores as the carrier.The result shows that the equivalent radius of pores and throats are 1-16 μm and 1.03-8.9 μm,respectively,and the throat length is 3.28-231.25 μm.The coordination number of pores concentrates around three,and the intersection point between the connectivity function and the X-axis is 3-4 μm,which indicate the macro-pores have good connectivity.During the single-channel flow,the pressure decreases along the direction of CH4 flow,and the flow velocity of CH4 decreases from the pore center to the wall.Under the dual-channel and the multi-channel flows,the pressure also decreases along the CH4 flow direction,while the velocity increases.The mean flow pressure gradually decreases with the increase of the distance from the inlet slice.The change of mean flow pressure is relatively stable in the direction horizontal to the bedding plane,while it is relatively large in the direction perpendicular to the bedding plane.The mean flow velocity in the direction horizontal to the bedding plane(Y-axis) is the largest,followed by that in the direction horizontal to the bedding plane(X-axis),and the mean flow velocity in the direction perpendicular to the bedding plane is the smallest.

Logistics Mode and Network Planning for Recycle of Crop Straw Resources

To realize the straw biomass industrialized development,it should speed up building crop straw resource recycle logistics network, increasing straw recycle efficiency,and reducing straw utilization cost. On the basis of studying straw recycle process,this paper presents innovative concept and property of straw recycle logistics network,analyses design thinking of straw recycle logistics network,and works out straw recycle logistics mode and network topological structure. Finally,it comes up with construction and operation strategies of the straw logistics network from infrastructure,organization network,and information platform.

A Spatio-Temporal Heterogeneity Data Accuracy Detection Method Fused by GCN and TCN

Spatio-temporal heterogeneous data is the database for decisionmaking in many fields,and checking its accuracy can provide data support for making decisions.Due to the randomness,complexity,global and local correlation of spatiotemporal heterogeneous data in the temporal and spatial dimensions,traditional detection methods can not guarantee both detection speed and accuracy.Therefore,this article proposes a method for detecting the accuracy of spatiotemporal heterogeneous data by fusing graph convolution and temporal convolution networks.Firstly,the geographic weighting function is introduced and improved to quantify the degree of association between nodes and calculate the weighted adjacency value to simplify the complex topology.Secondly,design spatiotemporal convolutional units based on graph convolutional neural networks and temporal convolutional networks to improve detection speed and accuracy.Finally,the proposed method is compared with three methods,ARIMA,T-GCN,and STGCN,in real scenarios to verify its effectiveness in terms of detection speed,detection accuracy and stability.The experimental results show that the RMSE,MAE,and MAPE of this method are the smallest in the cases of simple connectivity and complex connectivity degree,which are 13.82/12.08,2.77/2.41,and 16.70/14.73,respectively.Also,it detects the shortest time of 672.31/887.36,respectively.In addition,the evaluation results are the same under different time periods of processing and complex topology environment,which indicates that the detection accuracy of this method is the highest and has good research value and application prospects.

中高压直流断路器的研究与应用

多端直流系统及直流电网是未来柔性直流输配电系统的发展方向,其安全可靠稳定运行需要有直流断路器作为保障。虽然国内外研究人员提出了各种直流断路器技术方案,但目前市场上能够满足实际工程应用的直流断路器产品仍十分缺乏。该文对直流断路器的研究工作进行了梳理。首先,分析了不同技术方案采取的换流方式及性能,并介绍了直流断路器中的核心组件及其驱动保护。其次,对各类型的直流断路器拓扑结构进行了总结,并归纳出改进优化的方向。最后,对直流断路器研制的关键技术与未来的发展趋势进行了讨论和总结,为中高压直流断路器研制与应用提供参考。

公共汽电车复杂网络模型构建与特性分析——以淄博市为例

研究公共汽电车网络特性对于合理优化线路及站点布局具有重要作用。基于复杂网络理论,使用L空间、P空间和R空间三种建模方法,分别建立公共汽电车加权网络模型,并利用Gephi软件分析网络的节点度、平均路径长度、聚类系数等静态拓扑参数。进而对淄博市公共汽电车网络进行实例分析,并与不同规模城市进行对比。研究结果显示,淄博市市区公共汽电车站点网络的度分布符合指数分布,不具有明显的无标度特性,公共汽电车换乘网络和线路网络具有明显小世界特性。居民乘坐公共汽电车出行一次,平均需要经过13.77个站点并换乘1.32次,基本可以满足当前出行需求,但是与国家公交都市建设示范城市相比仍然存在邻近站点之间连接线路不足、具有换乘功能的站点较少、网络稳定性差等问题。

银企信贷复杂网络下的银行业系统性风险研究——基于高碳行业视角

碳减排压力下,高碳企业向低碳转型内生的“转型风险”可能成为引发下一场系统性金融风险的“绿天鹅”事件。基于2013-2022年14个高碳行业的银企贷款数据,首先采用“银企”二分网络法,以高碳企业预期违约率作为风险传染强度指标,纵向度量“银企”的风险传导路径。研究发现银企间网络规模逐年扩大,尾部风险突出集中于化工行业,且主要由股份制商业银行承受。其次运用“银银”映射网络法,以银行间共同风险敞口作为风险传染强度指标,横向度量“银银”的风险传导路径。研究发现城市商业银行与农村商业银行日渐成为系统重要性银行,风险承担愈加凸显;国有控股大型商业银行自身输出较大银行间尾部风险,其对风险的扩散或防御至关重要。最后基于复杂网络筛选出系统重要性银行与风险传染性银行,运用动态CoVaR法度量尾部溢出的系统性风险贡献强度,全面捕捉风险从高碳企业到金融机构间“自下而上的风险测度逻辑”,从而为监管部门构建“自上而下的风险监管逻辑”提供现实依据。在“双碳”战略下,应出台专门的信贷支持政策推动重点行业实施节能减排,立足“银企”信贷网络的全局开展差异化管理和全面风险评估,在逆周期缓冲资本监管框架的挂钩变量中引入高碳行业尾部风险的新视角。

区块链网络综述

区块链是典型的分布式系统,底层网络的性能和安全性至关重要.区块链网络的本质是P2P网络,然而在安全模型、传输协议和性能指标等方面与传统P2P网络存在明显差异.首先,针对区块链网络的传输流程进行全面、深入地分析,阐明区块链网络所面临的瓶颈挑战.其次,针对区块链网络拓扑结构和传输协议的最新研究工作,从节点异构性、编码方案、广播算法和中继网络等方面系统性地分类梳理,并归纳总结跨链网络实现和网络仿真工具.最后,探讨区块链网络的未来研究趋势.

An efficient reliability evaluation method for industrial wireless sensor networks

Aimed at the difficulties in accurately, comprehensively and systematically evaluating the reliability of industrial wireless sensor networks （WSNs）, a time-evolving state transition-Monte Carlo （TEST-MC） evaluation method and a novel network function value representation method are proposed to evaluate the reliability of the IWSNs. First, the adjacency matrix method is used to characterize three typical topologies of WSNs including the mesh network, tree network and ribbon network. Secondly, the network function value method is used to evaluate the network connectivity, and the TEST-MC evaluation method is used to evaluate network reliability and availability. Finally, the variations in the reliability, connectivity and availability of these three topologies are presented. Simulation results show that the proposed method can quickly analyze the reliability of the networks containing typical WSN topologies, which provides an effective method for the comprehensive and accurate evaluation of the reliability of WSNs.

高校全光校园网建设项目的研究与应用——以沈阳建筑大学为例

随着高校师生对信息化使用需求的断崖式增长,校园网越来越受到师生们的青睐。校园网可以为师生提供优质的信息,从而满足其办公和学习的需求。为进一步促进高校信息化网络建设,针对传统高校校园网存在的问题,发挥以太全光网技术的优势,探究以极简以太全光网技术为基础的全光校园网建设。以沈阳建筑大学全光校园网建设为例,根据师生的网络利用需求,构建全光校园网建设项目,绘制校园核心区域网络拓扑结构图,设计全光网建设项目内容,展示全光宿舍网建设项目的应用效果。

Calculation connectivity reliability of road networks based on recursive decomposition arithmetic

In order to decrease the calculation complexity of connectivity reliability of road networks, an improved recursive decomposition arithmetic is proposed. First, the basic theory of recursive decomposition arithmetic is reviewed. Then the characteristics of road networks, which are different from general networks, are analyzed. Under this condition, an improved recursive decomposition arithmetic is put forward which fits road networks better. Furthermore, detailed calculation steps are presented which are convenient for the computer, and the advantage of the approximate arithmetic is analyzed based on this improved arithmetic. This improved recursive decomposition arithmetic directly produces disjoint minipaths and avoids the non-polynomial increasing problems. And because the characteristics of road networks are considered, this arithmetic is greatly simplified. Finally, an example is given to prove its validity.

复杂网络均匀拓扑分割算法的结构能控性指数研究

结构能控性指数K是网络系统达到能控状态的控制时间步长的衡量指标。为更好地均衡复杂网络系统的控制时间步长与控制成本,采用均匀拓扑分割的算法,选取合适驱动节点集,得到更低的结构能控性指数的同时,均衡网络的控制时间步长与控制成本。算法的可行性通过证明系统分割后的子系统的结构能控性指数是原网络结构能控性指数的上界关系进行验证。通过仿真与最大匹配算法对ER随机网络和真实网络进行其有效性对比,仿真结果表明:本文算法达到均衡网络控制时间步长与控制成本的效果。

基于生态系统服务供需与拓扑结构分析的渭河流域生态网络优化

顾及区域自然资源禀赋和人类活动水平差异,优化生态网络成为缓解景观破碎化、提高连通性的有效途径,更保障了可持续发展目标的实现。在定量测度渭河流域2000、2010及2020年5项生态系统服务供需的基础上,引入景观生态学与复杂网络理论构建并分析该流域生态网络的时空格局及其网络拓扑结构特征,以供需比与源地节点的拓扑结构综合重要性之间的相关性为依据优化生态网络。结果表明:1)与2000年相比,2020年食物生产、土壤保持以及产水的供需比平均值分别上升70%、7%以及215%,而碳固定与生境质量则分别下降97%与1%。2)生态源地数量与占总面积比分别为125个和36%,生态阻力呈现“南低北高”的空间特征,约有280条平均长度为15 km的生态廊道,流域生态质量有所提升。3)2000、2010及2020年生态网络在面对蓄意攻击时,结构连通鲁棒性平均值依次为0.160、0.168以及0.150,说明2010年生态网络具有更稳定的网络结构;源地拓扑结构综合重要性与各类服务供需比均呈正相关,其中与碳固定服务供需比相关性最高,为0.51(P<0.001)。4)优化后的生态网络(2020年)在面对蓄意攻击时具有更高的连通鲁棒性,同时在一定攻击节点范围内表现出更为显著的“涌现”现象,优化后的网络具备更强的恢复力和缓冲力。研究结果可为渭河流域优化生态网络结构、提高生态系统抗干扰能力提供科学依据,也可为流域生态空间规划提供借鉴参考。

区域高速铁路网络性能的多维度评估指标对比研究

针对高速铁路网络性能评估问题,目前研究中存在多种维度和特征的评估指标,缺乏不同指标间的比较分析。选择站点拓扑维度指标(度中心性DC、接近中心性CC、介数B),站点功能维度指标(关键性SI、重要性SC、强度SS),以及网络整体维度指标(集聚系数、网络密度、平均路径长度),应用于京津冀、东北、西南3个区域的高速铁路网络性能评估,比较并分析了不同维度指标的特征、相关性和适用性。结果表明:SC指标可以量化不同区域高速铁路网络的差异,B指标对于拓扑简单的网络适用性差;DC,SI,SC,B 4个指标之间的相关性较强,而CC,SS2个指标与其他指标相关性较弱;京津冀地区高速铁路网络的连通性、密集程度均大于其他两地区,网络聚集系数评估区域高速铁路网络性能时会导致不合理的结果。

神经外科学在神经科学及脑网络研究中的重要作用

脑科学是现代最前沿的学科之一,受到全球研究者的高度重视。近年来有关脑科学的发展产生了巨大进步,尤其是脑网络的研究带来了破解大脑功能的新方向。脑科学的发展促进了神经外科学的理念更新,特别是脑网络的概念,使得神经外科手术需要更多地关注神经纤维束构成的脑网络结构,以更好地在术中保护重要的脑功能。脑科学的研究离不开对大脑的探究与观察,而神经外科学则是研究和通过手术治疗脑组织病变的科学,可在手术中直接地接触和研究大脑,并因此而发现重要的脑纤维及细胞的调配规律,进而对脑科学发展具有不可替代的重要作用。

基于拓扑结构分析的断层连通性评价——以川南泸州中区深层页岩气储层多级断层为例

川南深层页岩气是中国天然气增储上产的重要领域。断层连通性是影响深层页岩气储层渗透性能、单井产能的重要因素,前期多针对断层形态、组合样式开展研究,鲜有断层连通性的系统量化评价。研究以川南泸州中区五峰组页岩气储层多级断层为研究对象,利用拓扑结构分析方法研究断层网络拓扑结构,并对其连通性进行定量评价,结果显示:泸州中区五峰组断层发育,断层网络分支的平均连接点数为1.12,可形成高渗通道,有利于页岩气的运移。研究区中部及南部断层产状分散度、断层长度分散度和断层密度均较大,连接型节点、分支数量多,有利于提高断层连通性,其连通性评价结果优于其他区域,具备一定的潜在高产井可能。

数据驱动下的声学器件音质优化

音质是声学器件声音表现的重要衡量标准.但音质的优化过程需要对大量频点的响应进行协同优化,造成优化问题的可求解性较差.该文提出了一种数据驱动下的声学通道拓扑优化设计方法,可实现声-结构系统中的声频响快速预测,进而借助显式拓扑优化技术实现声学器件的音质优化.通过人工神经网络对结构几何参数、激励频率与声频响之间的非线性关系进行建模,以可移动变形组件(moving morphable components,MMC)法中的结构几何参数、激励频率为输入变量,以声压频响作为输出变量,通过训练多层前馈网络建立了声频响的人工神经网络模型.所得结果可以有效地将目标频带内的声压级范围差从44.89 dB缩小至6.49 dB,相较于传统优化方法,求解速度约为之前的16.3倍,表明了当前方法对音质优化问题的快速求解具有明显效果.

基于神经网络同步学习的功率模块散热器拓扑优化快速迭代方法

随着功率模块集成化程度的提高,其散热结构优化已成为研发中的关键。拓扑优化可通过变换散热器形貌、结构来最大化地提升散热效果,因此受到了广泛关注。但在拓扑优化过程中,每步迭代均需要计算模块与散热器温度分布,占用较庞大的计算资源和计算时间。为加速传统散热器拓扑优化进程,在基于传统固体各向同性材料惩罚SIMP(solid isotropic material with penalization)散热器拓扑优化方法的基础上,提出一种嵌套神经网络NN(neural network)同步学习的快速迭代方法。首先,构建散热器基于编码器-解码器结构的NN预测模型,即基于散热器形貌迭代进化过程实现优化结构的快速预测;其次,将NN模型与散热器SIMP拓扑优化流程相嵌套,利用迭代过程中的中间形貌同步训练NN;最后,针对单芯片、两芯片模块结构,对比所提方法与传统迭代方法的拓扑优化结果,验证了所提NN同步学习方法的准确性和快速性。

基于CUSUM改进算法的实际供热管网泄漏故障分级诊断

为了能够对供热管网泄漏故障进行及时和有效的诊断,提高管网泄漏位置的搜索效率,本文基于CUSUM改进算法,提出了通过管网拓扑结构的自由组合进行泄漏分级诊断的方法。以某城区集中供热管网为研究对象,将其拆分成5种拓扑结构并建立各自的管网水力工况模型,并选取4个1点泄漏工况和4个2点泄漏工况进行了验证分析。结果表明:在保证供热管网泄漏诊断模型压力、流量的仿真值与实际运行数据的最大相对误差绝对值不超过10%的条件下,该方法的泄漏位置诊断准确率达到了75%,验证了该方法应用于实际管网的可行性。