Complex Network Perspective Research Articles

Exploring the risk propagation mechanisms of supply chain for prefabricated building projects

Prefabricated building (PB) is an innovative construction method with significant advantages in environmental protection, energy saving, productivity increase, and quality improvement. The complexity of the prefabricated building project supply chain (PBPSC) also induces risks leading to the failure of PBP. Existing researches consider risks isolated and ignores the interactions between stakeholders of PBPSC that can lead to risk propagation and management failures. This study integrated epidemic models with complex networks to explore risk propagation mechanisms in PBPSC. The hierarchical structure of PBPSC was transited into a complex network for analyzing the features of the risk propagation process and the risk propagation capacity of initial infection nodes. The analysis results indicated that risk propagation and risk recovery were medium and often overlooked, which caused risk propagation in PBPSC. When major PBP contractors and construction enterprises were affected by risks, risk propagation was more likely to occur in PBPSC. This study was a meaningful attempt to analyze the risk propagation mechanisms from the perspective of complex networks in PBPSC. Based on the analysis results, this study revealed the critical risks and propagation characteristics of PBPSC for exploring the risk propagation mechanisms and response strategies to improve the risk response capacity of PBPSC.

Investigating Packet Transmission From the Perspective of Complex Networks Composed of Chaotic Circuits

Investigating Packet Transmission From the Perspective of Complex Networks Composed of Chaotic Circuits

Research on the game of fishermen's cooperative behavior in developing marine carbon sink fisheries from a complex network perspective

The development of marine carbon sink fisheries is both an important support to achieve the goal of net zero emissions as well as a hot topic concerning the livelihood of fishermen. Although it has been shown that there is great potential for carbon sinks in terms of environmental benefits, the lack of economic benefits in the short term is a hindrance that prevents marine carbon sink fisheries from being accepted by practitioners, especially fishermen groups. There is need to stimulate fishermen's enthusiasm for cooperative development of marine carbon sink fisheries and to promote marine carbon sink fisheries in order to achieve high efficiency and effectiveness. This paper adopts a complex network evolutionary game, based on the assumptions of WS small-world model on social network relationships, focuses on fishermen groups, and explores the dynamic evolutionary law of cooperative behavior diffusion in development of marine carbon sink fisheries. The results of the study show that (1) the government can accelerate the diffusion of cooperative behavior in the pre-development stage of marine carbon sink fisheries through subsidies, supplemented by certain punishments to curb the betrayal behavior, with the strength of the rewards and punishments dynamically adjusted according to the changes in the risks of implementation of marine carbon sink fisheries. (2) In the long term, higher value of marine carbon sink fisheries and their derived products is the essential demand of fishermen, which can effectively improve the depth of diffusion of fishermen's cooperation in developing marine carbon sink fisheries. (3) To avoid the spread of betrayal in the later stages of marine carbon sink fisheries development, the government can gradually reduce production subsidies and convert them into environmental subsidies in the sale process.

Features and Evolution of Global Energy Trade Patterns from the Perspective of Complex Networks

As an integral part of economic trade, energy trade is crucial to international dynamics and national interests. In this study, an international energy trade network is constructed by abstracting countries as nodes and representing energy trade relations as edges. A variety of indicators are designed in terms of networks, nodes, bilaterals, and communities to analyze the temporal and spatial evolution of the global energy trade network from 2001 to 2020. The results indicate that network density and strength have been steadily increasing since the beginning of the 21st century. It is observed that the position of the United States as the core of the international energy market is being impacted by emerging developing countries, thus affecting the existing trade balance based on topological analysis. The weighted analysis of bilateral relations demonstrates that emerging countries such as China, Brazil, and Saudi Arabia are pursuing closer cooperation. The community analysis reveals that an increasing number of countries possess strong energy trade capabilities, resulting in a corresponding increase in energy trade volumes.

Robustness of Double-Layer Group-Dependent Combat Network with Cascading Failure

The networked combat system-of-system (CSOS) is the trend of combat development with the innovation of technology. To achieve the combat effectiveness, studying the ability of CSOS to cope with external interference is of great importance. Here we report a modeling method of CSOS from the perspective of complex networks and explore the robustness of the combat network based on this. Firstly, a more realistic double-layer heterogeneous dependent combat network model is established. Then, the conditional group dependency situation is considered to design failure rules for dependent failure, and the coupling relation between the double-layer subnets is analyzed for overload failure. Based on this, the initial load and capacity of the node are defined, respectively, as well as the load redistribution strategy and the status judgment rules for the cascading failure model. Simulation experiments are carried out by changing the attack modes and different parameters, and the results show that the robustness of the combat network can be effectively improved by improving the tolerance limit of one-way dependency of the functional net, the node capacity of the functional subnet, and the tolerance of the overload state. The conclusions of this paper can provide a useful reference for network structure optimization and network security protection in the military field.

Structure, Resilience and Evolution of the European Air Route Network From 2015 to 2018

In spite of the dynamic nature of air transport, air route networks, i.e. the backbone used to organise aircraft flows, are expected to be mostly static, with small changes occasionally being introduced to improve the efficiency and resilience of the system. By leveraging a large data set of European flights comprising years 2015 to 2018, we analyse its structure and evolution from the perspective of complex networks, with the aim of firstly describing it, and secondly to confirm its static nature. Results depict a highly dynamic system, with major topological changes happening at the end of 2017. Peripheral links are usually more vulnerable, due to the lack of effective reroutings, as well as central regions; additionally, the overall resilience of the network is almost constant throughout time, in spite of an increase in traffic. We further test several hypotheses regarding the design considerations driving such evolution. Beyond specific operational insights, these results highlight the importance of taking into account the evolution of this network in the study of traffic flows.

Local-state routing in satellite constellation networks from the perspective of complex network

Local-state routing in satellite constellation networks from the perspective of complex network

Evolutionary game of cooperative behavior among social capitals in PPP projects: A complex network perspective

• The complex network is innovatively introduced in the study of the evolutionary of social capitals’ cooperative behavior; • The evolutionary trend of social capitals under different parameters in complex network are simulated; • Default penalty, network density and initial cooperation probability have different effects on the evolutionary of social capitals’ cooperative behavior; • Different network sizes have different sensitivities to each parameter. The relationship among social capitals is more complex in PPP projects, it is of great significance to clarify the evolutionary mechanism of cooperative behavior among them. The paper explores the evolutionary trend of social capitals’ cooperative behavior under different influences. It is found default penalty is positively related to the evolutionary of social capitals’ cooperative behavior; But the effect of network density is exactly the opposite; Under certain limits, initial cooperation probability has a positive effect on the emergence of cooperation; In addition, network size has different sensitivities to default penalty and network density. The larger the network size is, the stronger the sensitivity to default penalty; The opposite is true for network density. The research results will enrich the research perspective of social capitals’ cooperative behavior evolutionary and help to provide a new idea for promoting long-term stable cooperation between social capitals and improving the efficiency of PPP projects.

The evolution of public participation under dynamic government intervention in nuclear NIMBY events: a network evolutionary game method

The frequent occurrence of nuclear NIMBY events seriously affects social stability and the development of the nuclear power industry. Exploring the evolutionary development of nuclear NIMBY events and their control strategies is an important proposition. Different from recent studies on the influence of static government intervention into public participation in the collective action of NIMBY events, this paper aims to analyze how dynamic government interventions affect the decisions of the public from the perspective of complex networks. To better understand the dynamic rewards and punishments, the motivation of the public in nuclear NIMBY events is treated as a cost-benefit decision-making process. Then, a network evolutionary game model (NEGM) is built to analyze the strategy selection of all participants who are connected by an interaction network of the public. In addition, the drivers of the evolution of public participation in nuclear NIMBY events are analyzed with computational experiments. The results indicate the following: (a) Under dynamic punishment conditions, the probability of public participation in protests decreases with the increase in the upper bound of punishment. (b) Static reward measures can better control the development of nuclear NIMBY events. However, under dynamic reward conditions, there is no obvious effect with the increase in the reward ceiling. (c) The effect of the combination of government reward and punishment strategies is different in different network sizes. At the same time, with the continuous expansion of the scale of the network, the effect of government intervention worsens.

Using Space-L complex network model for public transportation supply and demand analysis in Taipei metropolitan area

As an important means of transportation in modern cities, public transportation plays an important role in people’s travel and the economic development of urban areas Harvey 1971 [1]. Many researchers apply the complex network theory to urban public transport network, construct complex networks and view the operation of urban public transport from the perspective of complex networks. The study established a complex network model of BUS, MRT (metro), LRT (light rail) and Multi-vehicle. And based on the weighted analysis of the actual passenger traffic, the weighted complex network model which conforms to the actual travel characteristics is obtained, and the relationship between the public transport station and the surrounding land use in Taipei metropolitan area is discussed.

Extreme risk spillovers among traditional financial and FinTech institutions: A complex network perspective

Extreme risk spillovers among traditional financial and FinTech institutions: A complex network perspective

Complex network of eye movements during rapid automatized naming.

Although the method of visualizing eye-tracking data as a time-series might enhance performance in the understanding of gaze behavior, it has not yet been thoroughly examined in the context of rapid automated naming (RAN). This study attempted, for the first time, to measure gaze behavior during RAN from the perspective of network-domain, which constructed a complex network [referred to as gaze-time-series-based complex network (GCN)] from gaze time-series. Hence, without designating regions of interest, the features of gaze behavior during RAN were extracted by computing topological parameters of GCN. A sample of 98 children (52 males, aged 11.50 ± 0.28 years) was studied. Nine topological parameters (i.e., average degree, network diameter, characteristic path length, clustering coefficient, global efficiency, assortativity coefficient, modularity, community number, and small-worldness) were computed. Findings showed that GCN in each RAN task was assortative and possessed "small-world" and community architecture. Additionally, observations regarding the influence of RAN task types included that: (i) five topological parameters (i.e., average degree, clustering coefficient, assortativity coefficient, modularity, and community number) could reflect the difference between tasks N-num (i.e., naming of numbers) and N-cha (i.e., naming of Chinese characters); (ii) there was only one topological parameter (i.e., network diameter) which could reflect the difference between tasks N-obj (i.e., naming of objects) and N-col (i.e., naming of colors); and (iii) when compared to GCN in alphanumeric RAN, GCN in non-alphanumeric RAN may have higher average degree, global efficiency, and small-worldness, but lower network diameter, characteristic path length, clustering coefficient, and modularity. Findings also illustrated that most of these topological parameters were largely independent of traditional eye-movement metrics. This article revealed the architecture and topological parameters of GCN as well as the influence of task types on them, and thus brought some new insights into the understanding of RAN from the perspective of complex network.

Water distribution network expansion: an evaluation from the perspective of complex networks and hydraulic criteria

Abstract The expansion of water distribution networks is nowadays essential to meet the pressing population growth in many cities worldwide. With the subsequent increase in water demand, the hydraulic behaviour of a water supply system can change dramatically due to the significant head losses in the pipes caused by the larger flows released by pumping systems and reservoirs to supply the higher water consumption of the network. Strategical studies are necessary to delimit risk regions where a demand increase may affect the system too negatively. To analyse expansion scenarios with the lowest risk of failure and damage for the supply network operations, this research studies hydraulic performance and connectivity under various demand increase scenarios using calculations of complex network metrics together with relevant hydraulic criteria. For these calculations, this research, developed in Python, uses, respectively, the NetworkX 2.5 and WNTR 0.3.0 packages. The C-Town network is employed as a case study, and demand increasing scenarios are implemented on 30 nodes along the peripheral regions of the network to simulate the growth of the cities. Then, these scenarios are evaluated using the TOPSIS methodology, thus determining the best and worst sectors to expand the capacity of the network.

Research on Structure Features of Supply Chain from the Perspective of Complex Network

With the rapid development of global manufacturing industry, many manufacturers begin to cooperate with each other. In China, a large number of foreign-funded enterprises in the automobile industry have settled in the Chinese mainland to set up factories and cooperate with local manufacturers. It is a significant task to find a way to optimize the structure of the complex supply network in the manufacturing industry. The paper selects the data on the share ratio relationship between enterprises in the automotive supply chain network published in the China Automotive Industry Yearbook, and selects appropriate software to analyze the topology structure characteristics of the supply chain network. Through numerical analysis, we can conclude that the structure features of supply chain networks can help us identify the hidden dangers of important nodes and point out the problems existing in the supply.

Impact of anti-dumping on global embodied air emissions: a complex network perspective.

After the rise of trade protectionism, anti-dumping has become a common means of political and trade games between countries. Global supply chains move production emissions between countries or regions through trade. In the context of carbon neutrality, anti-dumping measures representing the right to trade may become a tool for the game of emission rights between countries. Therefore, it is very important to study the environmental effects of anti-dumping to cope with global climate change and promote national development. Taking a sample of 189 countries and regions from the EORA input-output table with a study period of 2000-2016, we use the complex network, multi-regional input-output and panel regression models to verify the impact of anti-dumping on air emission transfer by constructing an anti-dumping network and an embodied air emission network. The results show that the initiator of anti-dumping can use anti-dumping to realize the cross-border transfer of ecological costs, reduce the burden of emission reduction and save more on emission quota. Developing countries lacking the right to speak in trade will increase the export volume of commodities after being subjected to a large number of anti-dumping sanctions, thus paying higher ecological costs and consuming more emission quotas. From a global perspective, additional emissions from product production can further contribute to global climate change.

Exploring the structural characteristics of intra-urban shared freight network and their associations with socioeconomic status

In recent years, shared freight systems have emerged in many cities as a new modality of freight transportation. However, little attention has been paid to the impact of a city’s socioeconomic status on the characteristics of a shared freight network. To fill this gap, in this study, the structural characteristics of an intra-urban shared freight network are measured from the perspective of complex networks, and the correlations between network structure and socioeconomic status are examined. A case study is conducted in Hong Kong using large amounts of GPS trajectory data for freight vehicles and socioeconomic data. The results show that socioeconomic variables such as population size, percentage of elderly residents, percentage of residents with a marital status classified as “other” (i.e., separated, widowed, or divorced), and percentage of residents employed in the tertiary sector have distinct correlations with the structural characteristics. These correlations display spatial non-stationarity. This research can potentially assist decision-makers in improving the operating efficiency of shared freight systems and the governance of digital freight transport.

Key Points-in-Time Identification of Gold Futures Market: A Complex Network Approach

Important nodes can determine the internal structure of complex networks and reveal the internal relationships of real-world systems, and identifying key nodes in complex networks is one of the important research areas of complex network science. As the king of commodities, changes in the price of gold significantly impact the economic development of various countries. Especially in the early stages of the outbreak of war between Russia and Ukraine, the price of gold futures has been greatly impacted, and the systemic risks are gradually spreading. In this paper, a gold future price series is mapped into a visibility graph (VG), the characteristics of the gold price time series and key points-in-time, have been explored from the perspective of complex network. First, according to the data structure characteristics of gold futures, this paper converts the closing prices of gold futures of the New York Mercantile Exchange into a complex network through the VG model. Then, by using the complex network model to further delve into the price of gold futures, it is found that the degree distribution of the gold futures network follows a power-law distribution, and has obvious scale-free characteristics. Finally, this paper uses the visual network node shrinking algorithm and the technique for order preference by similarity to ideal solution (TOPSIS) analysis method to identify the key nodes of the gold futures visual map to find the key time nodes in the timeline of gold futures market. Analysis of the key time nodes of this market by four methods reveals that the repetition rate of the key time nodes in the methods’ top 10 ranking is as high as 82.5%, indicating that the results obtained in this paper are robust. This study introduces a new model to describe the characteristics of gold futures price series, one which can find key time nodes in gold futures prices and provide potential help for predicting gold futures prices.

Finding spatial and temporal features of delay propagation via multi-layer networks

Air traffic system is a typical complex network with dynamic delay propagation between airports. However, difficulties in measuring delay propagation strength and constructing rational networks make investigating the features of delay propagation based on real data from the perspective of complex network is rarely seen. In this paper, using two largest real-world flights dataset of China and the USA over a period of two months in 2018 (from Jul. to Aug.), we construct the delay propagation networks among airports by calculating causality relationship between delay time series of airports. We identify the multilayer structures of networks by k-core decomposition and reveal that a core layer with a few of tightly connected airports dominants delay propagation in the whole systems. Through the analysis on motifs, bidirectional edges are found to be the culprit to expand the scope of delay propagation from airport pairs to local structures. At the system level, we analyze the properties of communities and found that airports geographically close to each other are likely to be classified into a delay propagation community, while the delay propagation between communities is mainly affected by the air traffic flow between them. Moreover, through the comparisons of structures for the delay propagation networks on different days, we reveal the temporal dependence of delay propagation that the more serious the delay propagation in one day, the more similar it will be to that in the next day. Finally, the usefulness of features found is assessed through applying them to predict the delay propagation in the future.

Blockchain Data Analysis from the Perspective of Complex Networks: Overview

Cryptocurrency based on blockchain technology has gradually become a choice for people to invest in, and several users have participated in the accumulation of massive transaction data. Complete transaction records in blockchains and the openness of data provide researchers with opportunities to mine and analyze data in blockchains. Network modeling and analysis of cryptocurrency transaction records are common methods in blockchain data analysis. The analysis of attribute graphs can provide insights into various economic indicators, illegal activities, and general Internet security, among others. Accordingly, this article aims to summarize and analyze the literature on cryptocurrency transaction data from the perspective of complex networks. To provide systematic guidance for researchers, we put forward a blockchain data analysis framework based on the introduction of the relevant background and reviewed the work from five aspects: blockchain data model, data acquisition on blockchains, existing analysis tools, available insights, and common analysis methods. For each aspect, we introduce the research problems, summarize the methods, and discuss the results and findings. Finally, we present future research points and several open questions in the study of cryptocurrency transaction networks.

Complex Network Analysis of China National Standards for New Energy Vehicles

Standards are technical measures to regulate and promote sustainability. China National Standards for new energy vehicles (NEV) are developing at an increasing rate. We explored the functions and citation network the China national standards from a complex-network perspective. Different types of standards were clustered and citation relationships were identified based on standards’ document analyses. In this paper, the evolution of standard nodes and citation links are presented, and implications for future standardization work are proposed. In total, 114 existing standards were identified through desktop research and network analysis by using the Gephi ForceAtlas2 algorithm. This study can be helpful for future standardization in areas such as autonomous driving and carbon-related standards based on citation-network analysis.