Artykuły w czasopismach: „Propagation risk”

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Yan, Huining, Hua Li, Qiubai Sun i Yuxi Jiang. "Propagation and control of congestion risk in scale-free networks based on information entropy". PLOS ONE 19, nr 3 (22.03.2024): e0300422. http://dx.doi.org/10.1371/journal.pone.0300422.

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To study the propagation pattern of congestion risk in the traffic network and enhance risk control capabilities, a model has been developed. This model takes into account the probabilities of five threats (the risk occurrence probability; the risk of loss; the unpredictability of risk; the uncontrollability of risk; the transferability of risk) in the traffic network to define the risk entropy and determine the risk capacity, analyze the mechanism of congestion risk propagation, and explore the impact of risk resistance, the average degree of risk capacity at intersections, and the degree of correlation on congestion risk propagation. Further, a control method model for risk propagation is proposed. Numerical simulation results demonstrate that the risk resistance parameter θ can inhibit the propagation of congestion risk during traffic congestion. The highest efficiency in controlling risk propagation is achieved when θ reaches a threshold value θ*. Furthermore, the average degree of intersection risk capacity α shows a positive correlation with θ* and a negative correlation with control efficiency. However, the degree of association ω has a negative effect on risk propagation control, decreasing the degree of association between nodes aids in risk propagation control.

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Zhang, Xuejun, Shuaizhe Zhao i Hao Mei. "Analysis of Airport Risk Propagation in Chinese Air Transport Network". Journal of Advanced Transportation 2022 (1.03.2022): 1–13. http://dx.doi.org/10.1155/2022/9958810.

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In recent years, due to the close coupling between airports, airport risk propagation has become a huge challenge. However, it has not been fully understood on the network level. Airport risk can be transferred through other airports owing to connected resources. In this study, we consider two risk factors including airport delay and saturation and propose a risk coupling model based on a clustering algorithm to fit the index and form risk series. To understand the risk propagation mechanism, we build risk propagation networks based on the Granger Causality test, and we apply complex network theory to analyze the evolution of the risk propagation network. We study the regular pattern of risk propagation from perspectives of time and space. Through network analysis, we find four time stages in the risk propagation process and the participation of airports in risk propagation has a positive correlation with airport sizes. In addition, more large airports tend to prevent risk propagation in unoccupied and normal situations, while small airports perform better than large airports in busy situations. Via the conclusion, our work can assist airlines or air traffic managers in controlling the scale of risk propagation before its key time turning point. By identifying the critical airport level and related factors in risk propagation, they can also reduce single airport risk and risk participation through corresponding risk control measures, finally avoiding the large-scale spread of risk and reducing delay or cancellation of more flights.

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Xu, Junke, Jiwei Zhu i Jiancang Xie. "Study on the Evolution of Risk Contagion in Urban River Ecological Management Projects Based on SEIRS". Water 15, nr 14 (19.07.2023): 2622. http://dx.doi.org/10.3390/w15142622.

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The risk transmission mechanisms of urban river ecological management engineering projects are examined in this study. Using the Susceptible Exposed Infectious Recovered Susceptible (SEIRS) model for risk transmission, a model of risk propagation delay for urban river ecological management engineering projects on scale-free networks is developed, which takes into account the effects of risk propagation and delay. We conducted a steady-state analysis of the model and obtained the basic reproduction number R. When R > 1, the equilibrium point of risk outbreak is stable, and when R < 1, the equilibrium point of risk disappearance is stable. Numerical simulations of the model were conducted using the MATLAB2022b to reveal the dynamic propagation patterns of risk in urban river ecological management engineering projects. The research results show that the steady-state density of the infected nodes in the network increases with the increase in the effective propagation rate and the propagation delay time; the propagation delay reduces the risk propagation threshold in the network and accelerates the occurrence of the equilibrium state of risk outbreak. There is a correlation between the transmission rate of latent nodes and the transmission rate of infected nodes, and the effective transmission rate of latent nodes has a greater influence on risk propagation. The spread of risk in the network can be effectively controlled and mitigated with targeted immunity for susceptible nodes. This article, based on the theory of complex networks and the mean-field theory, takes into account the propagation delay and spreading of latent nodes. Building a D-SEIRS model for risk propagation broadens the research perspective on urban river ecological management risk propagation.

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He, Zhenggang, Jing-Ni Guo i Jun-Xiang Xu. "Cascade Failure Model in Multimodal Transport Network Risk Propagation". Mathematical Problems in Engineering 2019 (6.12.2019): 1–7. http://dx.doi.org/10.1155/2019/3615903.

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The cascade failure theory is introduced into the risk propagation problem of the multimodal transport network in order to study the inherent law of risk propagation and provide theoretical support for the safety management of multimodal transport networks. Firstly, this paper analyses the characteristics of the multimodal transport network and concludes that the risk of the multimodal transport network belongs to failure risk. Secondly, the applicability of cascade failure theory is expounded. Based on cascade failure theory, a risk propagation model of the multimodal transport network is established. Through simulation experiments, the risk propagation of the multimodal transport network is analyzed from the differences of node distribution and node type. The process is analyzed, and the results show that different node distributions and different types of risk source nodes will have an impact on the risk propagation process. The influence of four types of node distributions on the risk propagation effect is in the following order: increasing type > concave-convex type ≈ balanced type > decreasing type. The influence of four types of source nodes on the risk propagation effect is in the following order: transportation type > transporting type > storage type > assistant type.

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Song, Yue, Naiding Yang, Yanlu Zhang i Jingbei Wang. "Suppressing risk propagation in R&D networks: the role of government intervention". Chinese Management Studies 13, nr 4 (4.11.2019): 1019–43. http://dx.doi.org/10.1108/cms-07-2018-0621.

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Purpose This paper aims to explore what factors influence the possibility of internal and external risk propagation in R&D networks and investigate how government intervention moderates the associations between the influencing factors and risk propagation. Design/methodology/approach The authors divided government intervention into directive and facilitative intervention and adopted an empirical research approach in this study. They collected 228 questionnaires from managers and R&D personnel participating in R&D projects in Shanghai and Jiangsu province through e-mail and in person. The data were used to carry out multiple regression analysis to test hypotheses. Findings The results show that the probability and consequence of risks positively affect the possibility of internal and external risk propagation; risk perception and transformation ability negatively influence the possibility of internal and external risk propagation; both directive and facilitative intervention weaken the relationship between the probability of risks and internal risk propagation when they are high than low the association between transformation ability and internal risk propagation is weaker when directive intervention is high than low, whereas facilitative intervention presents the insignificant moderation effect on the relationships between risk perception ability and internal and external risk propagation. Originality/value This study provides a distinctive theoretical perspective for risk conduction theory, government intervention theory and risk management. It also offered managers and the government a clear understanding of how to reduce or avoid risk propagation by leveraging directive and facilitative government intervention.

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Han, Yuanwen, Jiang Shen, Xuwei Zhu, Bang An, Fusheng Liu i Xueying Bao. "Study on the Mechanism of Safety Risk Propagation in Subway Construction Projects". Sustainability 16, nr 2 (17.01.2024): 796. http://dx.doi.org/10.3390/su16020796.

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Under the development trend of complexity and systematization of metro construction, there is an increasing number of risk factors potentially affecting construction safety, which has led to frequent accidents in metro construction projects, and the road to high-quality and sustainable development of metro construction is full of challenges. One of the essential reasons is that the propagation mechanism of safety risk factors in metro construction under hidden and delayed effects is not yet clear. This paper combines the theory of complex network and propagation dynamics and constructs a subway construction safety risk propagation model based on considering the hidden and delayed characteristics of construction safety risk propagation, which reveals the dynamic propagation law of subway construction safety risk and puts forward feasible coping strategies. The findings evince that the delay time T significantly affects the propagation behavior of risk and the achievement of the equilibrium state in the network. The transmissibility of the risk factor within the hidden state holds a pivotal sway over the entirety of risk propagation, and the latency in transmission significantly expedites the propagation of risk throughout the network. It is recommended that project managers monitor and warn safety state nodes and hidden state nodes to block the spread of risk in the network and control the delay time of risk in the network in time to reduce the probability of risk occurrence. This study significantly promotes the resilient management of safety risks in metro construction.

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Chen, Tingting, Yan Li, Xiongfei Jiang i Lingjie Shao. "Spatiotemporal Patterns of Risk Propagation in Complex Financial Networks". Applied Sciences 13, nr 2 (14.01.2023): 1129. http://dx.doi.org/10.3390/app13021129.

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The methods of complex networks have been extensively used to characterize information flow in complex systems, such as risk propagation in complex financial networks. However, network dynamics are ignored in most cases despite systems with similar topological structures exhibiting profoundly different dynamic behaviors. To observe the spatiotemporal patterns of risk propagation in complex financial networks, we combined a dynamic model with empirical networks. Our analysis revealed that hub nodes play a dominant role in risk propagation across the network and respond rapidly, thus exhibiting a degree-driven effect. The influence of key dynamic parameters, i.e., infection rate and recovery rate, was also investigated. Furthermore, the impacts of two typical characteristics of complex financial systems—the existence of community structures and frequent large fluctuations—on the spatiotemporal patterns of risk propagation were explored. About 30% of the total risk propagation flow of each community can be explained by the top 10% nodes. Thus, we can control the risk propagation flow of each community by controlling a few influential nodes in the community and, in turn, control the whole network. In extreme market states, hub nodes become more dominant, indicating better risk control.

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Ernst, Oliver G., Alois Pichler i Björn Sprungk. "Wasserstein Sensitivity of Risk and Uncertainty Propagation". SIAM/ASA Journal on Uncertainty Quantification 10, nr 3 (16.08.2022): 915–48. http://dx.doi.org/10.1137/20m1325459.

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Fuh, Cheng-Der, i Chu-Lan Michael Kao. "Credit Risk Propagation in Structural-Form Models". SIAM Journal on Financial Mathematics 12, nr 4 (styczeń 2021): 1340–73. http://dx.doi.org/10.1137/20m135340x.

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Cui, Bo, Meilong Le i Jinfu Zhu. "Review of the network risk propagation research". Aeronautics and Aerospace Open Access Journal 3, nr 2 (13.05.2019): 66–74. http://dx.doi.org/10.15406/aaoaj.2019.03.00082.

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Huang, C. Derrick, Ravi S. Behara i Qing Hu. "Managing Risk Propagation in Extended Enterprise Networks". IT Professional 10, nr 4 (lipiec 2008): 14–19. http://dx.doi.org/10.1109/mitp.2008.90.

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Liu, Yang, i Jingxin Liang. "Research on Risk Propagation in Complex Supply Chain Networks Based on SEIR Model". Frontiers in Business, Economics and Management 7, nr 3 (3.03.2023): 245–54. http://dx.doi.org/10.54097/fbem.v7i3.5586.

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The complexity of supply chain network structure makes the risk propagation among the enterprises in the supply chain more and more complicated. This paper constructs a SEIR risk propagation model for complex supply chain networks based on the analytical idea of contagion model, which reveals the risk propagation mechanism of supply chain networks from a macro perspective. The article verifies the existence of risk propagation threshold and the stability of different equilibrium points by analyzing the basic regeneration number, equilibrium point and stability of the model; explores the effectiveness of different parameters on the basic regeneration number by combining sensitivity analysis; and verifies them by using MATLAB simulation software. The results show that the basic regeneration number is a key factor affecting the risk propagation, and the risk diffusion in this system can be effectively curbed by controlling the basic regeneration number.

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Matsumoto, Hiroyuki, Hitoshi Mikada i Masanori Suzuki. "Excitation Process of the 2004 Indian Ocean Tsunami Determined from Seismic Fault Rupture". Journal of Disaster Research 1, nr 1 (1.08.2006): 136–41. http://dx.doi.org/10.20965/jdr.2006.p0136.

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We simulated the tsunami that had took place after the 2004 Sumatra-Andaman earthquake for two fault models - one from teleseismic body wave inversion and the other from tsunami data. After including the dynamic behavior of the seafloor by fault rupture propagation in the tsunami excitation process in detail, we found the difference in tsunami wave heights from the two fault models, in particular due to the difference in slip distribution. We then estimated the effects of the dynamic behavior due to fault rupture propagation, changing the initial conditions of tsunami simulation. Although the effects of dynamic contribution due to seismic fault rupture on tsunami propagating across the Indian Ocean were found to be negligible, the effect of seismic fault rupture propagation contributes to the arrival time of the tsunami because of the huge size of the seismic fault plane. A fault model based on seismic data, however, still cannot explain the tsunami captured by the satellite.

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Zhao, Changxiao, Wei Zhang, Fangzheng Dong, Jun Dai i Lei Dong. "Research on Resource Allocation Method of Integrated Avionics System considering Fault Propagation Risk". International Journal of Aerospace Engineering 2022 (22.08.2022): 1–19. http://dx.doi.org/10.1155/2022/8652818.

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The integrated modular avionics (IMA) system has coupled cross-linked support characteristics between physical resource entities and logical functions, and the existing resource allocation methods, which mainly consider system performance and resource utilization, do not consider the associated impact of fault propagation among resource entities. Aiming at the fault propagation risk in the resource allocation process of the IMA system, a hierarchical model of the IMA system is established. The fault propagation behavior caused by coupling association during the physical realization of the function layer logical architecture is analyzed, and the impact of different resource allocation methods on the fault propagation behavior is determined. Secondly, resource capacity constraints are established according to the resource requirement for hosted function, and the fault propagation risk model of the IMA system is constructed by considering the fault propagation impact factor, the relative importance of nodes, and the function safety criticality. The resource allocation method is evaluated according to the fault propagation risk model, and a heuristic algorithm is applied to optimize the resource allocation method of the IMA system. The simulation results show that the average propagation probability of the optimized resource allocation scheme decreases by 17.4%, and the overall fault propagation risk of the resource network decreases by 50.3%, indicating that the proposed resource allocation method can effectively improve the safety of the IMA system.

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Wang, Yang, i Gui Jiang Duan. "Engineering Change Propagation Analysis Based on Linkage Model in Complex Product Development". Applied Mechanics and Materials 271-272 (grudzień 2012): 887–96. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.887.

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To handle change propagations during complex product development, an analysis framework based on linkage model was proposed. Firstly linkage was defined to encapsulate the relations among product characteristics, and methods of linkage identification from multi-dimensions and linkage model construction were given. Then how to identify change propagation paths step by step in open scene and how to identify change propagation paths with improved mouse maze algorithm in closed scene were discussed. In the following a quantitative evaluation method of change impact risk was advanced. Finally an example of carrier robot moving structure design change was provided to validate this method.

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Li, Tengjiao, Hongzhuan Chen, Jie Yuan, Jingye Qian i Abdul Waheed Siyal. "Quality Risk Propagation of Complex Product Collaborative Manufacturing Supply Chain Network Based on CN and SoV". Discrete Dynamics in Nature and Society 2020 (15.12.2020): 1–16. http://dx.doi.org/10.1155/2020/8889903.

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The collaborative development of complex products has gradually developed into a “main manufacturer-suppliers” mode, under which the manufacturing enterprises form a complex product collaborative manufacturing supply chain network. Quality risks which bring enormous hidden danger to the product quality can be propagated and accumulate along the supply chain. It is of great significance to quantify the propagation mechanism of quality risk between supply chain network nodes and identify the key quality risk factor that causes fluctuation of product quality. This study for the first time applies the SoV into the research on quality risk propagation of complex product collaborative manufacturing supply chain network. Firstly, this paper uses the CN to construct a complex product collaborative manufacturing supply chain network according to its characteristics. Secondly, on the basis of SoV, the quality risk propagation model is established. Thirdly, we put forward a method to identify the key quality risk factors of supply chain network based on the risk propagation effect. Lastly, a numerical simulation is given to verify the effectiveness of the model and its identification method. The results reveal that the quality risk propagation includes the vertical propagation within enterprises and the horizontal propagation from the lower-level enterprises to the upper-level enterprises of the supply chain. The quality risks of an enterprise are determined by its own quality risk factors and the quality risk passed by the lower-level enterprises.

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Berger, J. R., J. W. Dally, R. deWit i R. J. Fields. "A Strain Gage Analysis of Fracture in Wide Plate Tests of Reactor Grade Steel". Journal of Pressure Vessel Technology 115, nr 4 (1.11.1993): 398–405. http://dx.doi.org/10.1115/1.2929547.

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A new method of fracture analysis is described. Strains recorded by gages in the immediate vicinity of a propagating crack are analyzed. From the analysis, crack tip position, propagation toughness, and crack velocity are determined. The analysis procedure Is demonstrated using data from the dynamic fracturing of a large-scale, wide plate test. The results are then used to describe the propagation toughness-crack velocity-temperature relation for the 2.25 Cr-1 Mo steel used in the test.

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Song, Yue, Naiding Yang, Yanlu Zhang i Jingbei Wang. "Do more structural holes lead to more risk propagation in R&D networks?" Management Decision 58, nr 1 (13.01.2020): 39–57. http://dx.doi.org/10.1108/md-07-2018-0767.

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Purpose The purpose of this paper is twofold: first, to explore how the number of structural holes influences the possibility of risk propagation in R&D networks; and second, to investigate how the specific context of tie strength and common cognition moderate the association between structural holes and risk propagation. Design/methodology/approach This study focuses on how structural holes influence risk propagation under the specific context of relationship and cognitive dimension by drawing on social capital theory. Risk sharing and risk perception as mediating variables are employed in the proposed conceptual model. The authors issued questionnaires to managers and R&D personnel participating in R&D projects and collaboration in Shanghai and Jiangsu province through e-mail and face to face. The data were used to carry out multiple regression analysis to test hypotheses. Findings The results show that relationship between structural holes and risk propagation of R&D network is U-shaped. Risk perception and risk sharing partially mediate the relationship between structural holes and risk propagation. Tie strength significantly moderates the relationship between structural holes and risk sharing, but insignificantly moderates the association between structural holes and risk perception. Common cognition significantly moderates the associations between structural holes and risk sharing, and structural holes and risk perception, respectively. Originality/value This study provides a distinctive theoretical perspective for social capital and risk management. It also offers managers a clear understanding of how to reduce or to avoid risk propagation by jointly leveraging the number of structural holes, tie strength and common cognition.

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Tansel, Berrin. "PFAS risk propagation terminology in spatial and temporal scales: Risk intensification, risk attenuation, and risk amplification". Science of The Total Environment 835 (sierpień 2022): 155503. http://dx.doi.org/10.1016/j.scitotenv.2022.155503.

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Tansel, Berrin. "PFAS risk propagation terminology in spatial and temporal scales: Risk intensification, risk attenuation, and risk amplification". Science of The Total Environment 835 (sierpień 2022): 155503. http://dx.doi.org/10.1016/j.scitotenv.2022.155503.

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Zhai, Wansheng. "Research on Risk Propagation in Fresh E-commerce Supply Chain Based on Complex Networks". International Journal of Global Economics and Management 3, nr 1 (9.05.2024): 11–20. http://dx.doi.org/10.62051/ijgem.v3n1.02.

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In recent years, the rapid growth of the fresh e-commerce industry has introduced several potential risk factors to the supply chain that necessitate preventative measures. This paper aims to study the risk propagation within the fresh e-commerce supply chain and propose strategies for risk control. Firstly, a dual local world fitness network model is constructed by combining the fitness model with the local world model. This model is then validated, showing consistency with the actual network. Building upon this, an improved SEIRS risk propagation model is developed, and the basic reproduction number is calculated to simulate the risk propagation within the fresh e-commerce supply chain. The results indicate that the degree of risk propagation is positively correlated with the initial infection rate, risk outbreak rate, and loss of immunization rate, while negatively correlated with the risk recovery rate and risk elimination rate.

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Cheng, Yusi, Jingfeng Yuan, Lei Zhu i Wei Li. "Risk Propagation Model and Simulation of Schedule Change in Construction Projects: A Complex Network Approach". Complexity 2020 (30.11.2020): 1–12. http://dx.doi.org/10.1155/2020/8854609.

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Construction schedules play an important role in construction project management. However, during construction activities, risks may arise due to unexpected schedule changes, resulting in the ineffective delivery of projects. This study aims to reveal the law of schedule change risk propagation and to analyze the effects on the risk propagation through numerical simulations. First, construction projects are represented by activity-on-node (AON) networks. A model of risk propagation is then built based on a susceptible-infected (SI) model considering the effects of the nodal characteristics on the propagation process. Next, the model is tested on a real-world project to examine cascading failures with varying parameters. The experimental results demonstrate that the model is effective in identifying the activities most capable of affecting a project schedule and evaluating the impact of schedule change risk propagation. This study will provide a basis for enhancing the robustness of AON networks and controlling the propagation of schedule change risks.

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He, Song, Can Zhang, Wei Guo i Li-Dong Zhai. "Worms Propagation Modeling and Analysis in Big Data Environment". International Journal of Distributed Sensor Networks 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/985856.

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The integration of the Internet and Mobile networks results in huge amount of data, as well as security threat. With the fragile capacity of security protection, worms can propagate in the integration network and undermine the stability and integrity of data. The propagation of worm is a great security risk to massive amounts of data in the integration network. We propose a kind of worm propagating in big data environment named BD-Worm. BD-Worm consumes computing resources and gets privacy information of users, which causes huge losses to our working and living. This paper constructs an integration network topology model and designs the BD-Worm propagating in the big data environment. To analyze the propagation of BD-Worm, we conduct a simulation and provide some recommendations to contain the widespread of BD-Worm according to the simulation results.

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ZHANG, Yong-Zheng. "Risk Propagation Model for Assessing Network Information Systems". Journal of Software 18, nr 1 (2007): 137. http://dx.doi.org/10.1360/jos180137.

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Ojha, Ritesh, Abhijeet Ghadge, Manoj Kumar Tiwari i Umit S. Bititci. "Bayesian network modelling for supply chain risk propagation". International Journal of Production Research 56, nr 17 (4.05.2018): 5795–819. http://dx.doi.org/10.1080/00207543.2018.1467059.

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Shin, KwangSup, YongWoo Shin, Ji‐Hye Kwon i Suk‐Ho Kang. "Risk propagation based dynamic transportation route finding mechanism". Industrial Management & Data Systems 112, nr 1 (27.01.2012): 102–24. http://dx.doi.org/10.1108/02635571211193662.

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Serrano, Alejandro, Rogelio Oliva i Santiago Kraiselburd. "Risk propagation through payment distortion in supply chains". Journal of Operations Management 58-59, nr 1 (marzec 2018): 1–14. http://dx.doi.org/10.1016/j.jom.2018.01.003.

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Li, Xixi. "Cascading Propagation Path of Vinyl Chloride Process Risk Based on Complex Network". Academic Journal of Science and Technology 9, nr 2 (23.02.2024): 149–54. http://dx.doi.org/10.54097/cxw6gf62.

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In the production of vinyl chloride, small parameter fluctuations may lead to large-scale cascade fluctuations, causing serious economic losses and casualties, in order to ensure the safety and stability of production, it is necessary to study the cascade fluctuation propagation path of vinyl chloride production process. In this paper, a complex network model of vinyl chloride production process is constructed based on complex network theory, and the concept of comprehensive degree considering network direction is introduced to identify important nodes in the network: secondly, the fluctuation overload propagation probability and material hazard degree of the edge are used to define the fluctuation overload propagation intensity of the edge; finally, according to the fluctuation overload propagation intensity, the risk propagation path of cascading fluctuations under different overload modes is obtained by using ant colony algorithm, it provides a basis for the prevention of cascade overload and the selection and protection of key monitoring nodes.

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Takagaki, Masakazu, i Toshiya Nakamura. "Fatigue Crack Modeling and Simulation Based on Continuum Damage Mechanics". Journal of Pressure Vessel Technology 129, nr 1 (10.03.2006): 96–102. http://dx.doi.org/10.1115/1.2388993.

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Numerical simulation of fatigue crack propagation based on fracture mechanics and the conventional finite element method requires a huge amount of computational resources when the cracked structure shows a complicated condition such as the multiple site damage or thermal fatigue. The objective of the present study is to develop a simulation technique for fatigue crack propagation that can be applied to complex situations by employing the continuum damage mechanics (CDM). An anisotropic damage tensor is defined to model a macroscopic fatigue crack. The validity of the present theory is examined by comparing the elastic stress distributions around the crack tip with those obtained by a conventional method. Combined with a nonlinear elasto-plastic constitutive equation, numerical simulations are conducted for low cycle fatigue crack propagation in a plate with one or two cracks. The results show good agreement with the experiments. Finally, propagations of multiply distributed cracks under low cycle fatigue loading are simulated to demonstrate the potential application of the present method.

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Kang, Chang Muk, Yoo S. Hong, Woonghee Tim Huh i Wanmo Kang. "Risk Propagation Through a Platform: The Failure Risk Perspective on Platform Sharing". IEEE Transactions on Engineering Management 62, nr 3 (sierpień 2015): 372–83. http://dx.doi.org/10.1109/tem.2015.2427844.

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Andria, Joseph, Giacomo di Tollo i Jaan Kalda. "Propagation of Bankruptcy Risk over Scale-Free Economic Networks". Entropy 24, nr 12 (24.11.2022): 1713. http://dx.doi.org/10.3390/e24121713.

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The propagation of bankruptcy-induced shocks across domestic and global economies is sometimes very dramatic; this phenomenon can be modelled as a dynamical process in economic networks. Economic networks are usually scale-free, and scale-free networks are known to be vulnerable with respect to targeted attacks, i.e., attacks directed towards the biggest nodes of the network. Here we address the following question: to what extent does the scale-free nature of economic networks and the vulnerability of the biggest nodes affect the propagation of economic shocks? We model the dynamics of bankruptcies as the propagation of financial contagion across the banking sector over a scale-free network of banks, and perform Monte-Carlo simulations based on synthetic networks. In addition, we analyze the public data regarding the bankruptcy of US banks from the Federal Deposit Insurance Corporation. The dynamics of the shock propagation is characterized in terms of the Bank Failures Diffusion Index, i.e., the average number of new bankruptcies triggered by the bankruptcy of a single bank, and in terms of the Shannon entropy of the whole network. The simulation results are in-line with the empirical findings, and indicate the important role of the biggest banks in the dynamics of economic shocks.

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Mu, Liming, Yingzhi Zhang i Qiyan Zhang. "Risk Evaluation Method Based on Fault Propagation and Diffusion". Mathematics 11, nr 19 (26.09.2023): 4083. http://dx.doi.org/10.3390/math11194083.

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The high reliability demand of the machining center emphasizes the accuracy of the fault risk evaluation. In the traditional fault risk evaluation research of the machining center, the influence of fault mode is mostly based on subjective recommendation or does not consider the propagation and diffusion of fault, which makes the risk evaluation results different from the real situation. Therefore, this paper presents a framework to evaluate the fault risk for machining center components. A certain type of machining center is considered as a case study. The fault mode frequency ratio of components is calculated by fault mode analysis. The fault rate calculation is conducted based on the Johnson method. Considering that different fault modes have different influences on fault propagation breadth and depth, the hypergraph theory is used to build a hypernetwork model. The propagation and diffusion influence degree are defined to describe the propagation and diffusion process of faults. Then, the comprehensive influence degree of fault mode is calculated. The risk evaluation is realized by considering the component fault rate, fault mode frequency ratio, and the comprehensive influence degree of fault mode. The method proposed in this paper can provide a reference for the formulation of risk strategies for the machining center.

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Zhu, Jianjun, Yamin Cheng i Yuhuai Zhang. "Risk Propagation Mechanism Research Based on SITR Model of Complex Supply Networks". International Journal of Information Systems and Supply Chain Management 14, nr 3 (lipiec 2021): 18–38. http://dx.doi.org/10.4018/ijisscm.2021070102.

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Supply chain risk management is an important topic in supply chain management. The authors investigate the rules and characteristics of risk propagation in complex supply networks. Aiming at the characteristics of complex supply chain with complex structure and large risk consequences, considering the different impact capabilities and different anti-risk capabilities of each enterprise node, this paper proposes a SITR (susceptible-infected-temporarily removed-completely removed) risk propagation model based on weighted networks. After the dynamic analysis of the proposed model, numerical simulation is performed, and a supply chain risk control strategy is proposed according to the simulation results. The research shows that the enterprise's complete recovery rate and risk infection rate have a greater impact on the risk propagation in the supply chain network. Enterprises should increase their awareness of risk management and control, improve their complete recovery rate, and reduce their risk of infection.

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Sun, Rui, i Wan Bo Luo. "Rumor Propagation Model for Complex Network with Non-Uniform Propagation Rates". Applied Mechanics and Materials 596 (lipiec 2014): 868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.596.868.

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Considering propagation characteristics and affecting factors of rumor in real-world complex networks, this paper described different propagation rates of different nodes by introducing the rumor acceptability function. Based on mean-field theory, this paper presented a rumor propagation model with non-uniform propagation rate, and then simulated the behaviour of rumor propagation on scale-free network and calculated the propagation thresholds by corresponding dynamics equation. Theoretical analysis and simulation results show that nodes with different rumor acceptability could lead to slowing the spread of rumors, make positive propagation threshold arise, and effectively contain the outbreak and reduce the risk of rumors.

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Yang, Yunfeng, Guohua Chen i Yuanfei Zhao. "A Quantitative Framework for Propagation Paths of Natech Domino Effects in Chemical Industrial Parks: Part II—Risk Assessment and Mitigation System". Sustainability 15, nr 10 (19.05.2023): 8306. http://dx.doi.org/10.3390/su15108306.

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This is the second part of the quantitative framework for the propagation paths of Natech domino effects in chemical industrial parks, which focuses on risk assessment and a mitigation system based on the propagation path probabilities obtained from Part I. In this paper, the risk assessment model for the propagation paths of the domino effects induced by natural disasters are developed, and the risk level is quantitatively analyzed using individual risk and social risk indexes and compared with the risk acceptance standard to determine whether the risk in the plant area is at the risk acceptance level. Furthermore, the chain-cutting disaster mitigation model for domino effects induced by Natech events and the full-life-cycle mitigation system are proposed, and the effectiveness of mitigation measures is also evaluated. The case analysis results show that Natech events and multi-level domino effects can increase the risk to an unacceptable level, and taking corresponding mitigation measures could reduce the risk to an acceptable level.

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Huo, Liang’an, Hongyuan Guo i Yingying Cheng. "Supply chain risk propagation model considering the herd mentality mechanism and risk preference". Physica A: Statistical Mechanics and its Applications 529 (wrzesień 2019): 121400. http://dx.doi.org/10.1016/j.physa.2019.121400.

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Tirado-Ramos, Alfredo, i Chris Kelley. "Simulation of HIV Infection Propagation Networks". International Journal of Agent Technologies and Systems 5, nr 1 (styczeń 2013): 53–63. http://dx.doi.org/10.4018/jats.2013010104.

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Simulating the transmission of HIV requires a model framework that can account for the complex nature of HIV transmission. In this paper the authors present the current state of the art for simulating HIV with agent-based models and highlight some of the significant contributions of current research. The authors then propose opportunities for future work including their plan that involves identifying and monitoring high-risk drug users that can potentially initiate high-risk infection propagation networks.

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Portarapillo, Maria, i Almerinda Di Benedetto. "Methodology for risk assessment of COVID-19 pandemic propagation". Journal of Loss Prevention in the Process Industries 72 (wrzesień 2021): 104584. http://dx.doi.org/10.1016/j.jlp.2021.104584.

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Kuang, Yan, Xiaobo Qu i Shuaian Wang. "Propagation and dissipation of crash risk on saturated freeways". Transportmetrica B: Transport Dynamics 2, nr 3 (25.06.2014): 203–14. http://dx.doi.org/10.1080/21680566.2014.930675.

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Yang, Hsin-Feng, Chih-Liang Liu i Ray Yeutien Chou. "Interest rate risk propagation: Evidence from the credit crunch". North American Journal of Economics and Finance 28 (kwiecień 2014): 242–64. http://dx.doi.org/10.1016/j.najef.2014.03.010.

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Wang, Zhe, Hong Yao, Guoli Yang i Jun Du. "Failure risk propagation and protection schemes in coupled systems". Chaos, Solitons & Fractals 80 (listopad 2015): 62–75. http://dx.doi.org/10.1016/j.chaos.2015.06.005.

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Chen, Wenying, Jinyu Yang, Mohammad T. Khasawneh, Jiaping Fu i Baoping Sun. "Rules of incidental operation risk propagation in metro networks under fully automatic operations mode". PLOS ONE 16, nr 12 (16.12.2021): e0261436. http://dx.doi.org/10.1371/journal.pone.0261436.

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The frequent interruptions of network operation due to any incident suggest the necessity to study the rules of operational risk propagation in metro networks, especially under fully automatic operations mode. In this study, risk indicator computation models were developed by analyzing risk propagation processes within transfer stations and metro networks. Moreover, indicator variance rules for a transfer station and different structural networks were discussed and verified through simulation. After reviewing the simulation results, it was concluded that under the impacts of both sudden incident and peak passenger flow, the more the passengers coming from platform inlets, the longer the non-incidental line platform total train operation delay and the higher the crowding degree. However, train headway has little influence on non-incidental line platform risk development. With respect to incident risk propagation in a metro network, the propagation speed varies with network structure, wherein an annular-radial network is the fastest, a radial is moderately fast, and a grid-type network is the slowest. The conclusions are supposed to be supports for metro operation safety planning and network design.

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Cao, Shoufeng, Kim Bryceson i Damian Hine. "An Ontology-based Bayesian network modelling for supply chain risk propagation". Industrial Management & Data Systems 119, nr 8 (9.09.2019): 1691–711. http://dx.doi.org/10.1108/imds-01-2019-0032.

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Purpose Supply chain risks (SCRs) do not work in isolation and have impact both on each member of a chain and the performance of the entire supply chain. The purpose of this paper is to quantitatively assess the impact of dynamic risk propagation within and between integrated firms in global fresh produce supply chains. Design/methodology/approach A risk propagation ontology-based Bayesian network (BN) model was developed to measure dynamic SCR propagation. The proposed model was applied to a two-tier Australia-China table grape supply chain (ACTGSC) featured with an upstream Australian integrated grower and exporter and a downstream Chinese integrated importer and online retailer. Findings An ontology-based BN can be generated to accurately represent the risk domain of interest using the knowledge and inference capabilities inherent in a risk propagation ontology. In addition, the analyses revealed that supply discontinuity, product inconsistency and/or delivery delay originating in the upstream firm can propagate to increase the downstream firm’s customer value risk and business performance risk. Research limitations/implications The work was conducted in an Australian-China table grape supply chain, so results are only product chain-specific in nature. Additionally, only two state values were considered for all nodes in the model, and finally, while the proposed methodology does provide a large-scale risk network map, it may not be appropriate for a large supply chain network as it only follows the process flow of a single supply chain. Practical implications This study supports the backward-looking traceability of risk root causes through the ACTGSC and the forward-looking prediction of risk propagation to key risk performance measures. Social implications The methodology used in this paper provides an evidence-based decision-making capability as part of a system-wide risk management approach and fosters collaborative SCR management, which can yield numerous societal benefits. Originality/value The proposed methodology addresses the challenges in using a knowledge-based approach to develop a BN model, particularly with a large-scale model and integrates risk and performance for a holistic risk propagation assessment. The combination of modelling approaches to address the issue is unique.

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Ye, Qing, Yi Li i Ben Niu. "Risk Propagation Mechanism and Prediction Model for the Highway Merging Area". Applied Sciences 13, nr 14 (8.07.2023): 8014. http://dx.doi.org/10.3390/app13148014.

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The merging area is one of the most accident-prone areas on highways. After an accident occurs, the risk will propagate along the main road over a certain range and time. Therefore, the study of the propagation mechanism of accident risk will help to quantify the driving risk in this region. An effective risk prediction model is important for improving traffic control measures in this specific area. In this study, simulation experiments were conducted in SUMO (Simulation of Urban Mobility) to obtain the accident and risk propagation data in merging areas. Firstly, the Gaussian plume model was optimized for the merging area situation to determine and divide the impact range of the accidents. Then, different accident scenarios in the merging area and downstream were simulated with different input flow rates to study the time and speed of risk propagation in the three-level affected areas. Finally, LSTM (long short-term memory) and RNN (recurrent neural network) models were built to predict the accident risk in the merging area. The results showed that the LSTM model had higher accuracy. This study provides an innovative insight into the propagation process of merging area accidents. It is of benefit to the development of post-accident control measures.

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Seiler, Fritz A. "Error Propagation for Large Errors". Risk Analysis 7, nr 4 (grudzień 1987): 509–18. http://dx.doi.org/10.1111/j.1539-6924.1987.tb00487.x.

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Turner, Barry A. "Accidents and Nonrandom Error Propagation". Risk Analysis 9, nr 4 (grudzień 1989): 437–44. http://dx.doi.org/10.1111/j.1539-6924.1989.tb01254.x.

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Voloshyn, V. S., i O. V. Klenin. "Specificity of risk assessment in project management". Reporter of the Priazovskyi State Technical University. Section: Technical sciences, nr 45 (29.12.2022): 88–96. http://dx.doi.org/10.31498/2225-6733.45.2022.276241.

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The work is devoted to the issues of risk forecasting in project management systems. The paper proposes to use the analytical capabilities of neural networks of direct propagation. This is an option that allows you to take into account the influence of subjective factors when determining risk in project management. The model of such a network makes it possible to use bifurcation dependencies as a formula for activating synapses. This approach has its difficulties in training a neural network. It allows you to formalize its work in conditions of uncertainty of input signals for individual neurons. A formula for taking into account bifurcation dependencies when using them in neural networks of direct propagation is proposed. The scope of application of such a dependence in the training models of the neural network of direct propagation is shown. This is shown on the example of a project management system, where both the contractor and the customer have a subjective factor. The possibilities of such models for analyzing possible risks both in the creation and in the implementation of projects are shown. At the same time, the risk of losing any factors from among those that lead to the emergence of risk-forming scenarios and events is excluded. This shows how easy it is to take into account the uncertainty in signal activation systems when training a neural network. Such an approach can make it possible to find solutions in a selected area for a wide range of similar problems. However, the requirement for network architecture can be problematic because of its individuality for each type of task. For the selected system, key scenarios have been identified, including subjective ones, which depend on the actual output functions allocated through the work of the trained perceptron. They reflect the risk system in such projects. And we do this in a generalized version, without specification for design systems. The proposed model of a direct propagation network can be extended and specified for a variety of tasks of this type, differing only in the meaning of input signals as logical statements. In this aspect, the material can be of a methodological nature and be applied not only in project management, but also in training systems

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Mutha, Chetan, i Carol Smidts. "Basis for non-propagation domains, their transformations and their impact on software reliability". Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 232, nr 6 (26.12.2017): 535–58. http://dx.doi.org/10.1177/1748006x17744380.

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Fault propagation analysis is an important step in determining system reliability and defining fault tolerance strategies. Typically, in the early software design phases, the propagation probability for a fault is assumed to be one. However, the assumption that faults will always propagate highly underestimates reliability, and valuable resources may be wasted on fixing faults that may never propagate. To determine the fault propagation probability, a concept of flat parts is introduced. A flat part is a property of a function; when multiple functions containing flat parts interact with each other, these flat parts undergo a transformation. During this transformation, the flat parts may be killed, preserved, or new flat parts may be generated. Interval arithmetic-based rules to determine such flat part transformations are introduced. A flat part-based propagation analysis can be used to determine the reliability of a software system, or software-driven mechanical system expressed functionally. In addition, the information obtained through flat part-based propagation analysis can be used to add sensors within the flat parts to increase the probability of fault detection, thus increasing the robustness of the system under study.

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Krus, Daniel, i Katie Grantham Lough. "Function-based failure propagation for conceptual design". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 23, nr 4 (17.04.2009): 409–26. http://dx.doi.org/10.1017/s0890060409000158.

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AbstractWhen designing a product, the earlier the potential risks can be identified, the more costs can be saved, as it is easier to modify a design in its early stages. Several methods exist to analyze the risk in a system, but all require a mature design. However, by applying the concept of “common interfaces” to a functional model and utilizing a historical knowledge base, it is possible to analyze chains of failures during the conceptual phase of product design. This paper presents a method based on these common interfaces to be used in conjunction with other methods such as risk in early design to allow a more complete risk analysis during the conceptual design phase. Finally, application of this method is demonstrated in a design setting by applying it to a thermal control subsystem.

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Ongkowijoyo, Citra S., Hemanta Doloi i Anthony Mills. "Participatory-based risk impact propagation and interaction pattern analysis using social network analysis". International Journal of Disaster Resilience in the Built Environment 10, nr 5 (11.11.2019): 363–78. http://dx.doi.org/10.1108/ijdrbe-06-2017-0041.

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Purpose This paper aims to develop a novel risk analysis model that uses both participatory and computerized techniques to capture and model the dynamic of risk impact propagation and interaction pattern. Design/methodology/approach In this research, an integrated model, applying modified participatory method and novel dichotomize procedure in the perspectives of social network topological analysis, is developed. Findings Based on the analysis output, it is found that; (i) the risk propagation is characterized by its dynamic and non-linear impact pattern, and (ii) the risk interaction is distinguished based on the degree of connectedness between various risks. Research limitations/implications This research assumes that the risk impact propagation and interaction pattern within the risk network are static. Further research is required to analyze the risk network in dynamic circumstances. Practical implications This research contributes in delivering practical tools that could potentially provide a further path for developing mitigation strategy and policies that seek to address the complexity of risk phenomena, and thus enhance community resilience. Social implications This research reveals some underlying patterns of how the risk impact propagation and interaction pattern are structured. Thus, it can help decision-makers make formal arrangements of particular urban infrastructure (UI) governance visible toward building risk plan and mitigation strategies. Originality/value This research contributes to filling the risk management knowledge gap. It is suggested that analyzing risk using a network approach is suited to capture the intricate processes that shape the complexity of UI risk structural network. By validating the model, this research shows the applicability and capability of the model to improve both the RA accuracy and decision making effectiveness towards risk mitigation plan and strategy.

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