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Characterization and optimization of satellite complex networks based on hyperbolic space 认领 引用
1
作者 Yuanzhi He Huajun Fu +3 位作者 Di Yan Shanshan Feng Hongbo Chen Xuebin Zhuang 《Digital Communications and Networks》 SCIE EI CSCD 2025年第6期1689-1706,共18页
In recent years,the rapid advancement of mega-constellations in Low Earth Orbit(LEO)has led to the emergence of satellite communication networks characterized by a complex interplay between high-and low-altitude orbit... In recent years,the rapid advancement of mega-constellations in Low Earth Orbit(LEO)has led to the emergence of satellite communication networks characterized by a complex interplay between high-and low-altitude orbits and by unprecedented scale.Traditional network-representation methodologies in Euclidean space are insufficient to capture the dynamics and evolution of high-dimensional complex networks.By contrast,hyperbolic space offers greater scalability and stronger representational capacity than Euclidean-space methods,thereby providing a more suitable framework for representing large-scale satellite communication networks.This paper aims to address the burgeoning demands of large-scale space-air-ground integrated satellite communication networks by providing a comprehensive review of representation-learning methods for large-scale complex networks and their application within hyperbolic space.First,we briefly introduce several equivalent models of hyperbolic space.Then,we summarize existing representation methods and applications for large-scale complex networks.Building on these advances,we propose representation methods for complex satellite communication networks in hyperbolic space and discuss potential application prospects.Finally,we highlight several pressing directions for future research. 展开更多
关键词 Hyperbolic space Complex network Network representation Satellite communication network
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Global dynamics and optimal control of SEIQR epidemic model on heterogeneous complex networks 认领 引用
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作者 Xiongding Liu Xiaodan Zhao +1 位作者 Xiaojing Zhong Wu Wei 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第6期262-274,共13页
This paper investigates a new SEIQR(susceptible–exposed–infected–quarantined–recovered) epidemic model with quarantine mechanism on heterogeneous complex networks. Firstly, the nonlinear SEIQR epidemic spreading d... This paper investigates a new SEIQR(susceptible–exposed–infected–quarantined–recovered) epidemic model with quarantine mechanism on heterogeneous complex networks. Firstly, the nonlinear SEIQR epidemic spreading dynamic differential coupling model is proposed. Then, by using mean-field theory and the next-generation matrix method, the equilibriums and basic reproduction number are derived. Theoretical results indicate that the basic reproduction number significantly relies on model parameters and topology of the underlying networks. In addition, the globally asymptotic stability of equilibrium and the permanence of the disease are proved in detail by the Routh–Hurwitz criterion, Lyapunov method and La Salle's invariance principle. Furthermore, we find that the quarantine mechanism, that is the quarantine rate(γ1, γ2), has a significant effect on epidemic spreading through sensitivity analysis of basic reproduction number and model parameters. Meanwhile, the optimal control model of quarantined rate and analysis method are proposed, which can optimize the government control strategies and reduce the number of infected individual. Finally, numerical simulations are given to verify the correctness of theoretical results and a practice application is proposed to predict and control the spreading of COVID-19. 展开更多
关键词 epidemic spreading SEIQR model stability and sensitivity analysis heterogeneous complex networks optimal control
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GPIC:A GPU-based parallel independent cascade algorithm in complex networks 认领 引用
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作者 Chang Su Xu Na +1 位作者 Fang Zhou Linyuan Lü 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第3期20-30,共11页
Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model ... Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round simulations.To settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling strategies.Specifically,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC model.In addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational efficiency.The results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC method.Our experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research. 展开更多
关键词 complex networks information spreading independent cascade model parallel computing GPU
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Characteristics of complex network of heatwaves over China 认领 引用
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作者 Xuemin Shen Xiaodong Hu +2 位作者 Aixia Feng Qiguang Wang Changgui Gu 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第3期567-577,共11页
Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in differen... Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns. 展开更多
关键词 complex network heatwave spatiotemporal evolution characteristics
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Degree-Preserving Distance Compression and Topological Compressibility of Complex Networks 认领 引用
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作者 Jian-Hui Li Zu-Guo Yu Yu-Chu Tian 《Chinese Physics Letters》 SCIE EI CAS CSCD 2025年第12期24-32,共9页
Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly ... Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly optimized topologies.But the key problems arise:how to compress a network to best enhance its compactness,and what the compression limit of the network reflects?We abstract the topological compression of complex networks as a dynamic process of making them more compact and propose the local compression modulus that plays a key role in effective compression evolution of networks.Subsequently,we identify topological compressibility-a general property of complex networks that characterizes the extent to which a network can be compressed-and provide its approximate quantification.We anticipate that our findings and established theory will provide valuable insights into both dynamics and various applications of complex networks. 展开更多
关键词 local compr topological compression node interactionswhich network topologyreal accurately modeling real network dynamics compact highly optimized topologiesbut complex networks network dynamics
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Finite time hybrid synchronization of heterogeneous duplex complex networks via time-varying intermittent control 认领 引用
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作者 Cheng-Jun Xie Xiang-Qing Lu 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第4期354-363,共10页
This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid s... This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid synchronization of heterogeneous duplex complex networks.Therefore,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time.To be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite time.Finally,numerical examples are presented to illustrate the validness of theoretical results. 展开更多
关键词 finite time synchronization time-varying intermittent control duplex heterogeneous networks complex networks
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Modified Fixed-Time Synchronization Criteria of Complex Networks with Time-Varying Delays via Continuous or Discontinuous Control 认领 引用
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作者 WU Huan WU Ailong ZHANG Jin'e 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2025年第2期150-158,共9页
This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of ... This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of FxTS is independent of the initial values and parameters of the CNs,a modified fixed-time(FxT)stability theorem is proposed,where the ST is determined by an arbitrary positive number given in advance.Then,continuous controller and discontinuous controller are designed to realize the modified FxTS target of CNs.In addition,based on the designed controllers,CNs can achieve synchronization at any given time,or even earlier.And control strategies effectively solve the problem of ST related to the parameters of CNs.Finally,an appropriate simulation example is conducted to examine the effectiveness of the designed control strategies. 展开更多
关键词 complex networks settling time fixed-time synchronization controllers time-varying delays
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K-GCN for Identifying Key Nodes in Complex Networks 认领 引用
8
作者 Lin DONG Yufeng LU 《Journal of Mathematical Research with Applications》 CSCD 2025年第2期260-274,共15页
Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability ... Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability and accuracy. To address these challenges, this study introduces the K-GCN model, which integrates neighborhood k-shell distribution analysis with Graph Convolutional Network(GCN) technology to enhance key node identification in complex networks. The K-GCN model first leverages neighborhood k-shell distributions to calculate entropy values for each node, effectively quantifying node importance within the network. These entropy values are then used as key features within the GCN, which subsequently formulates intelligent strategies to maximize network connectivity disruption by removing a minimal set of nodes, thereby impacting the overall network architecture. Through iterative interactions with the environment, the GCN continuously refines its strategies, achieving precise identification of key nodes in the network. Unlike traditional methods, the K-GCN model not only captures local node features but also integrates the network structure and complex interrelations between neighboring nodes, significantly improving the accuracy and efficiency of key node identification.Experimental validation in multiple real-world network scenarios demonstrates that the K-GCN model outperforms existing methods. 展开更多
关键词 key nodes complex networks K-shell GCN
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Cluster synchronization of master-slave complex networks via adaptive feedback pinning control 认领 引用
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作者 LIU Ziping GONG Siyi 《上海师范大学学报（自然科学版中英文）》 2025年第4期389-400,共12页
This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling m... This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach. 展开更多
关键词 cluster synchronization time-varying master-slave complex networks delayed adaptive feedback control pinning control
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Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges 认领 引用 被引量：3
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作者 YANG Yinghui LI Jianhua +2 位作者 SHEN Di NAN Mingli CUI Qiong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第3期549-559,共11页
Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolvi... Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges（CNFNOEs） is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks（ILCN）. Secondly,the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method.Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE＇s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network,etc. 展开更多
关键词 complex network with fusion nodes and overlap edges（CNFNOEs） interlacing layered complex networks（ILCN） local world dynamic evolvement split saturation attraction factor
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Circulation system complex networks and teleconnections 认领 引用 被引量：28
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作者 龚志强 王晓娟 +1 位作者 支蓉 冯爱霞 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第7期495-503,共9页
In terms of the characteristic topology parameters of climate complex networks, the spatial connection structural complexity of the circulation system and the influence of four teleconnection patterns are quantitative... In terms of the characteristic topology parameters of climate complex networks, the spatial connection structural complexity of the circulation system and the influence of four teleconnection patterns are quantitatively described. Results of node degrees for the Northern Hemisphere （NH） mid-high latitude （30° N-90°N） circulation system （NHS） networks with and without the Arctic Oscillations （AO）, the North Atlantic Oscillations （NAO） and the Pacific-North American pattern （PNA） demonstrate that the teleconnections greatly shorten the mean shortest path length of the networks, thus being advantageous to the rapid transfer of local fluctuation information over the network and to the stability of the NHS. The impact of the AO on the NHS connection structure is most important and the impact of the NAO is the next important. The PNA is a relatively independent teleconnection, and its role in the NHS is mainly manifested in the connection between the NHS and the tropical circulation system （TRS）. As to the Southern Hemisphere mid-high latitude （30°S-90°S） circulation system （SHS）, the impact of the Antarctic Arctic Oscillations （AAO） on the structural stability of the system is most important. In addition, there might be a stable correlation dipole （AACD） in the SHS, which also has important influence on the structure of the SHS networks. 展开更多
关键词 complex network structural feature circulation system node degree
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Load-redistribution strategy based on time-varying load against cascading failure of complex network 认领 引用 被引量：9
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作者 刘军 熊庆宇 +2 位作者 石欣 王楷 石为人 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第7期371-377,共7页
Cascading failure can cause great damage to complex networks, so it is of great significance to improve the network robustness against cascading failure. Many previous existing works on load-redistribution strategies ... Cascading failure can cause great damage to complex networks, so it is of great significance to improve the network robustness against cascading failure. Many previous existing works on load-redistribution strategies require global information, which is not suitable for large scale networks, and some strategies based on local information assume that the load of a node is always its initial load before the network is attacked, and the load of the failure node is redistributed to its neighbors according to their initial load or initial residual capacity. This paper proposes a new load-redistribution strategy based on local information considering an ever-changing load. It redistributes the loads of the failure node to its nearest neighbors according to their current residual capacity, which makes full use of the residual capacity of the network. Experiments are conducted on two typical networks and two real networks, and the experimental results show that the new load-redistribution strategy can reduce the size of cascading failure efficiently. 展开更多
关键词 load redistribution time-varying load cascading failure complex networks
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Networked Knowledge and Complex Networks:An Engineering View 认领 引用 被引量：10
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作者 Jinhu Lü Guanghui Wen +2 位作者 Ruqian Lu Yong Wang Songmao Zhang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第8期1366-1383,共18页
Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based softw... Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based software engineering have undergone fundamental changes where the network plays an increasingly important role.Within this context,it is required to develop new methodologies as well as technical tools for network-based knowledge representation,knowledge services and knowledge engineering.Obviously,the term“network”has different meanings in different scenarios.Meanwhile,some breakthroughs in several bottleneck problems of complex networks promote the developments of the new methodologies and technical tools for network-based knowledge representation,knowledge services and knowledge engineering.This paper first reviews some recent advances on complex networks,and then,in conjunction with knowledge graph,proposes a framework of networked knowledge which models knowledge and its relationships with the perspective of complex networks.For the unique advantages of deep learning in acquiring and processing knowledge,this paper reviews its development and emphasizes the role that it played in the development of knowledge engineering.Finally,some challenges and further trends are discussed. 展开更多
关键词 Complex network knowledge graph networked knowledge neural network
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Traffic resource allocation for complex networks 认领 引用 被引量：9
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作者 凌翔 胡茂彬 +2 位作者 龙建成 丁建勋 石琴 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第1期583-588,共6页
In this paper, an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks. The network resources are the total node packet-delivering capacity and the total link bandwidth. An ... In this paper, an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks. The network resources are the total node packet-delivering capacity and the total link bandwidth. An analytical method is developed to estimate the overall network capacity by using the concept of efficient betweenness （ratio of algorithmic betweenness and local processing capacity）. Three network structures （scale-free, small-world, and random networks） and two typical routing protocols （shortest path protocol and efficient routing protocol） are adopted to demonstrate the performance of the proposed strategy. Our results show that the network capacity is reversely proportional to the average path length for a particular routing protocol and the shortest path protocol can achieve the largest network capacity when the proposed resource allocation strategy is adopted. 展开更多
关键词 complex network shortest path protocol efficient routing protocol resource allocation strategy
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Detecting community structure using label propagation with consensus weight in complex network 认领 引用 被引量：9
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作者 梁宗文 李建平 +1 位作者 杨帆 Athina Petropulu 《Chinese Physics B》 SCIE EI CAS CSCD 2014年第9期594-601,共8页
Community detection is a fundamental work to analyse the structural and functional properties of complex networks. The label propagation algorithm （LPA） is a near linear time algorithm to find a good community struc... Community detection is a fundamental work to analyse the structural and functional properties of complex networks. The label propagation algorithm （LPA） is a near linear time algorithm to find a good community structure. Despite various subsequent advances, an important issue of this algorithm has not yet been properly addressed. Random update orders within the algorithm severely hamper the stability of the identified community structure. In this paper, we executed the basic label propagation algorithm on networks multiple times, to obtain a set of consensus partitions. Based on these consensus partitions, we created a consensus weighted graph. In this consensus weighted graph, the weight value of the edge was the proportion value that the number of node pairs allocated in the same cluster was divided by the total number of partitions. Then, we introduced consensus weight to indicate the direction of label propagation. In label update steps, by computing the mixing value of consensus weight and label frequency, a node adopted the label which has the maximum mixing value instead of the most frequent one. For extending to different networks, we introduced a proportion parameter to adjust the proportion of consensus weight and label frequency in computing mixing value. Finally, we proposed an approach named the label propagation algorithm with consensus weight （LPAcw）, and the experimental results showed that the LPAcw could enhance considerably both the stability and the accuracy of community partitions. 展开更多
关键词 label propagation algorithm community detection consensus cluster complex network
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A self-organizing shortest path finding strategy on complex networks 认领 引用 被引量：9
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作者 沈毅 裴文江 +1 位作者 王开 王少平 《Chinese Physics B》 SCIE EI CAS 2009年第9期3783-3789,共7页
The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our met... The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our method, the shortest paths between the source node and the other nodes are found to be self-organized by comparing node temperatures. The computation complexity of the method scales linearly with the number of edges on underlying networks. The effects of the method on several networks, including a regular network proposed by Ravasz and Barabasi which is called the RB network, a real network, a random network proposed by Ravasz and Barabasi which is called the ER network and a scale-free network, are also demonstrated. Analytic and simulation results show that the method has a higher accuracy and lower computational complexity than the conventional methods. 展开更多
关键词 complex networks self-organization the shortest path thermal flux diffusion
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Rapid identifying high-influence nodes in complex networks 认领 引用 被引量：7
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作者 宋波 蒋国平 +1 位作者 宋玉蓉 夏玲玲 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第10期1-9,共9页
A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the unc... A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method（RIM）to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered（SIR） model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness,and eigenvector centrality methods. 展开更多
关键词 high-influence nodes dynamic model complex networks centrality measures
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LCH:A local clustering H-index centrality measure for identifying and ranking influential nodes in complex networks 认领 引用 被引量：7
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作者 Gui-Qiong Xu Lei Meng +1 位作者 Deng-Qin Tu Ping-Le Yang 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第8期566-574,共9页
Identifying influential nodes in complex networks is one of the most significant and challenging issues,which may contribute to optimizing the network structure,controlling the process of epidemic spreading and accele... Identifying influential nodes in complex networks is one of the most significant and challenging issues,which may contribute to optimizing the network structure,controlling the process of epidemic spreading and accelerating information diffusion.The node importance ranking measures based on global information are not suitable for large-scale networks due to their high computational complexity.Moreover,they do not take into account the impact of network topology evolution over time,resulting in limitations in some applications.Based on local information of networks,a local clustering H-index(LCH)centrality measure is proposed,which considers neighborhood topology,the quantity and quality of neighbor nodes simultaneously.The proposed measure only needs the information of first-order and second-order neighbor nodes of networks,thus it has nearly linear time complexity and can be applicable to large-scale networks.In order to test the proposed measure,we adopt the susceptible-infected-recovered(SIR)and susceptible-infected(SI)models to simulate the spreading process.A series of experimental results on eight real-world networks illustrate that the proposed LCH can identify and rank influential nodes more accurately than several classical and state-of-the-art measures. 展开更多
关键词 complex networks influential nodes local structure susceptible infected recovered model susceptible infected model
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Optimization-based topology identification of complex networks 认领 引用 被引量：7
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作者 唐圣学 陈丽 何怡刚 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第11期127-133,共7页
In many cases, the topological structures of a complex network are unknown or uncertain, and it is of significance to identify the exact topological structure. An optimization-based method of identifying the topologic... In many cases, the topological structures of a complex network are unknown or uncertain, and it is of significance to identify the exact topological structure. An optimization-based method of identifying the topological structure of a complex network is proposed in this paper. Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network. Then, an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem. Compared with the previous adaptive synchronization- based method, the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks. In some cases where the states of a complex network are only partially observable, the exact topological structure of a network can also be identified by using the proposed method. Finally, numerical simulations are provided to show the effectiveness of the proposed method. 展开更多
关键词 complex networks topology identification optimization particle swarm
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Aviation Accident Causation Analysis Based on Complex Network Theory 认领 引用 被引量：18
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作者 YUE Rentian LI Junwei HAN Meng 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第4期646-655,共10页
Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in th... Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in this paper.Through selecting 257 accident investigation reports,45 causative factors and nine accident types are obtained by the three-level coding process of the grounded theory,and the interaction of these factors is analyzed based on the“2-4”model.Accordingly,the aviation accident causation network is constructed based on complex network theory which has scale-free characteristics and small-world properties,the characteristics of causative factors are analyzed by the topology of the network,and the key causative factors of the accidents are identified by the technique for order of preference by similarity to ideal solution(TOPSIS)method.The comparison results show that the method proposed in this paper has the advantages of independent of expert experience,quantitative analysis of accident causative factors and statistical analysis of a lot of accident data,and it has better applicability and advancement. 展开更多
关键词 aviation safety accident causation complex network theory grounded theory “2-4”model
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