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Journal articles on the topic 'Diagramme de causalité'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Junglas, Peter. "Causality of System Dynamics Diagrams." SNE Simulation Notes Europe 26, no. 3 (2016): 147–54. http://dx.doi.org/10.11128/sne.26.tn.10343.

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2

BOUAZIZ, Yosra Jlaiel, and Daniel THIEL. "Enquête sur les mécanismes de pilotage des compétences dans le cadre de la mise en oeuvre de projets ERP en tunisie." Revue Française de Gestion Industrielle 32, no. 2 (2013): 63–84. http://dx.doi.org/10.53102/2013.32.02.696.

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Cette recherche s'intéresse aux décisions de pilotage des compétences dans le cadre de mise en oeuvre de projets ERP. Après une revue de littérature et une pré-enquête sur le terrain, nous avons lancé une enquête auprès de 31 chefs de projets en Tunisie. Cet échantillon représente 30% de la population totale visée, à savoir les entreprises ayant récemment implanté un ERP composé d'au moins trois modules. Une analyse statistique des données a été réalisée à partir de 651 décisions observées. Ces décisions ont également été formalisées qualitativement à l'aide de diagrammes de causalité permetta

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3

Zhang, Qin. "Probabilistic reasoning based on dynamic causality trees/diagrams." Reliability Engineering & System Safety 46, no. 3 (1994): 209–20. http://dx.doi.org/10.1016/0951-8320(94)90114-7.

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4

Wu, Bing, Luyao Kou, and Qi Ma. "Research on HFACS Based on Accident Causality Diagram." Open Journal of Safety Science and Technology 07, no. 02 (2017): 77–85. http://dx.doi.org/10.4236/ojsst.2017.72007.

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5

Wang, Hongchun. "A Fuzzy Reasoning Algorithm in Hybrid Causality Diagram." Journal of Algorithms & Computational Technology 6, no. 4 (2012): 623–38. http://dx.doi.org/10.1260/1748-3018.6.4.623.

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6

Eichler, Michael. "Granger causality and path diagrams for multivariate time series." Journal of Econometrics 137, no. 2 (2007): 334–53. http://dx.doi.org/10.1016/j.jeconom.2005.06.032.

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7

Jin, Feng, Jun Zhao, Chunyang Sheng, and Wei Wang. "Causality diagram-based scheduling approach for blast furnace gas system." IEEE/CAA Journal of Automatica Sinica 5, no. 2 (2018): 587–94. http://dx.doi.org/10.1109/jas.2017.7510715.

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8

Perdicoúlis, Anastássios, and Jake Piper. "Network and system diagrams revisited: Satisfying CEA requirements for causality analysis." Environmental Impact Assessment Review 28, no. 7 (2008): 455–68. http://dx.doi.org/10.1016/j.eiar.2007.08.004.

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9

Zhang, Chun You, and Xiao Qiang Wu. "Intrusion Scenario Dynamic Correlation Algorithm Based on Single Value Causality Diagram." Advanced Materials Research 926-930 (May 2014): 3063–67. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3063.

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In order to obtain the effective network intrusion alarm information, and reveal the intention of attackers, an intrusion scenario dynamic correlation algorithm is proposed based on single value causality diagram. According to the composition principle of single value causality diagram, the key factors of the cause and effect diagram are defined. By relating the alarm information of intrusion detection system, attack scenarios are constructed based on cause and effect diagram, and dynamic correction is conduct. Based on the MIT Lincoln laboratory data sets, the correlation test is done using t

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10

Zhou, Zu Xu. "Research on the Preventive Measures of Sports Injury Based on Causality Diagram and Analytic Hierarchy Process." Applied Mechanics and Materials 380-384 (August 2013): 1838–42. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1838.

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Because of the frequent occurrence of injury accident in the sports curriculum, the security of physical education cannot be ignored. So, this paper analyzes the factors of injury accident in physical education teaching process and proposes prevention measures. The establishment of security system in physical education is an urgent problem. This paper studies the causes and countermeasures of sports injury accidents based on two methods: causality diagram and analytic hierarchy process. The first section introduces the principles of causality diagram and hierarchical analysis in detail. The se

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11

Zhang, Boyi, Pengjian Shang, and Jinzhao Liu. "Transition-based complexity-entropy causality diagram: A novel method to characterize complex systems." Communications in Nonlinear Science and Numerical Simulation 95 (April 2021): 105660. http://dx.doi.org/10.1016/j.cnsns.2020.105660.

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12

Jia, Lulu, Yi Ren, Dezhen Yang, Qiang Feng, Bo Sun, and Cheng Qian. "Reliability analysis of dynamic reliability block diagram based on dynamic uncertain causality graph." Journal of Loss Prevention in the Process Industries 62 (November 2019): 103947. http://dx.doi.org/10.1016/j.jlp.2019.103947.

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13

Zhang, Qin. "A frequency and knowledge tree/causality diagram based expert system approach for fault diagnosis." Reliability Engineering & System Safety 43, no. 1 (1994): 17–28. http://dx.doi.org/10.1016/0951-8320(94)90092-2.

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14

Gaskell, Amy L., and Jamie W. Sleigh. "An Introduction to Causal Diagrams for Anesthesiology Research." Anesthesiology 132, no. 5 (2020): 951–67. http://dx.doi.org/10.1097/aln.0000000000003193.

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Abstract Making good decisions in the era of Big Data requires a sophisticated approach to causality. We are acutely aware that association ≠ causation, yet untangling the two remains one of our greatest challenges. This realization has stimulated a Causal Revolution in epidemiology, and the lessons learned are highly relevant to anesthesia research. This article introduces readers to directed acyclic graphs; a cornerstone of modern causal inference techniques. These diagrams provide a robust framework to address sources of bias and discover causal effects. We use the topical question of wheth

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15

Kocabas, Verda, and Suzana Dragicevic. "Enhancing a GIS Cellular Automata Model of Land Use Change: Bayesian Networks, Influence Diagrams and Causality." Transactions in GIS 11, no. 5 (2007): 681–702. http://dx.doi.org/10.1111/j.1467-9671.2007.01066.x.

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16

Scripcaru, Răzvan, Angela Digulescu, Leontin Tuță, and Alexandru Șerbănescu. "Discussion upon the Stationarity and the Causality of a Time Series Using the Phase Diagram Representation." Journal of Military Technology 2, no. 2 (2019): 11–16. http://dx.doi.org/10.32754/jmt.2019.2.02.

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17

Zhang, Mengyao, Deming Yu, Tianyu Wang, and Can Xu. "Coupling Analysis of Tunnel Construction Safety Risks Based on N-K Model and SD Causality Diagram." Buildings 13, no. 4 (2023): 1081. http://dx.doi.org/10.3390/buildings13041081.

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Tunnel construction is characterized by its large scale, long periods and vulnerability to environmental impact, which pose great challenges to tunnel construction safety. In order to analyze the coupling mechanism of tunnel construction safety risks and assess these risks, we conducted a study on the coupling evaluation of these risks in order to improve tunnel construction safety risk management. By analyzing 150 accident cases related to tunnel construction safety, an N-K model (natural killing model) was constructed to quantify the risk level of each coupling form from four aspects—personn

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18

Mutisari, Rini, Syafrial, Nuhfil Hanani, and Sujarwo. "Enhancing household rice farmers’ welfare under climate change conditions using loop diagrams of causality: A system thinking approach." IOP Conference Series: Earth and Environmental Science 1323, no. 1 (2024): 012009. http://dx.doi.org/10.1088/1755-1315/1323/1/012009.

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Abstract Climate change has hurt several sectors, but agriculture has been a tough hit. Small farmers are the people most affected by climate change because they have less access to resources and information. Their household welfare is lowered as a result, and they are unable to avoid the effects of climate change. To lessen the negative effects of climate change, farmers have to figure out how to adapt to it. This study uses a household economic model to examine the relationship between livelihood assets and strategic adaptation using the framework of systems thinking. This research has creat

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19

Bakti Nugraha, Arif. "Dynamic Decision-Making Model Analysis for Pandemic Spread Control Using Causal Loop Diagram." CoreID Journal 3, no. 1 (2025): 9–13. https://doi.org/10.60005/coreid.v3i1.91.

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Corona Virus Disease 2019 or better known as Covid 19 spreads very quickly and has become a pandemic for the world today. In its development process, it is very dynamic and complex, consisting of many interrelated and different components, each with its own purpose. As for the dynamic and complex issues in the spread of the Corona virus, the ability is absolutely necessary to limit the spread of the virus. For this reason, it is necessary to know the factors that influence and inhibit the spread of the virus as well as what strategies are needed and analyze the dynamic causality of these facto

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20

Oleg, Shinsky, Shalevska Inna, Kaliuzhnyi Pavlo, et al. "Principles of construction and identification of a multilevel system for monitoring parameters of technological cycle of casting." Eastern-European Journal of Enterprise Technologies 5, no. 1 (95) (2018): 25–32. https://doi.org/10.15587/1729-4061.2018.141303.

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For the creation of a multi-level system of integrated control and operational management of physical-chemical and technological casting processes, deterministic causality of technological objects was determined. These objects are involved in the processes of melting, ladle and heat treatment in the production of ductile iron castings. This made it possible to develop a block diagram of selection and optimization of key technological parameters, geometry of gating systems for the lost-foam casting. In order to ensure continuous control over a set of parameters of technological processes, equip

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21

Tambun, Toronata, Gatot Yudoko, and Leo Aldianto. "Mapping Workplace Inclusion in Hierarchical Collectivist Societies: A Causal Loop Diagram Approach." Systems 13, no. 5 (2025): 351. https://doi.org/10.3390/systems13050351.

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Workplace integration in hierarchical collectivist societies is shaped by structured social mechanisms rather than collectivist values alone. While collectivism is often assumed to foster inclusiveness, its structural manifestations regulate workplace inclusion through feedback loops of hierarchical loyalty, trust building, and kinship-based exclusivity. This study employs causal loop diagrams (CLDs) to conceptually map how cultural structures regulate workplace inclusion—not to assert empirical causality, but to illustrate the culturally grounded feedback loops in Indonesia and the Philippine

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22

Gholipour, Amir, Rita Fragoso, Ana Galvão, and David C. Finger. "Mapping the causality of interacting perceptions for nature-based solution and sludge treatment reed bed: A causal loop diagram in Iceland." Nature-Based Solutions 3 (December 2023): 100049. http://dx.doi.org/10.1016/j.nbsj.2023.100049.

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23

ZAINAL ABIDIN, NORHASLINDA, SHRI DEWI APPLANAIDU, MOHAMMED BABA ABDULLAHI, and SURIANIE BAKAR. "UNDERSTANDING PADDY PRODUCTIVITY AT MADA ESTATE FROM A SYSTEM DYNAMICS PERSPECTIVE: A MAPPING TOOL OF CAUSAL LOOP DIAGRAM." JOURNAL OF SUSTAINABILITY SCIENCE AND MANAGEMENT 18, no. 2 (2023): 81–1012. http://dx.doi.org/10.46754/jssm.2023.02.007.

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The Muda Agricultural Development Authority (MADA) paddy estate project represents Malaysia’s national effort to enhance food security. However, the Economic Transformation Programme (ETP) by Malaysia falls short of attaining the 10 MT/Ha paddy productivity potential. Amidst rising food insecurity, national efforts have focused on improving the efficiency of domestic productivity, this study specifically assessed factors influencing paddy productivity under the MADA estate project. Against the econometric technique, the causal loop diagram (CLD) in the system dynamics (SD) approach was used to

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24

Apertet, Y. "Causality in thermoelectric systems: Insights from block diagrams." European Physical Journal Plus 131, no. 12 (2016). http://dx.doi.org/10.1140/epjp/i2016-16434-6.

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25

Sborlini, German Fabricio Roberto. "Geometry and causal flux in multi-loop Feynman diagrams." Suplemento de la Revista Mexicana de Física 3, no. 2 (2022). http://dx.doi.org/10.31349/suplrevmexfis.3.020703.

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In this review, we discuss recent developments concerning efficient calculations of multi-loop multi-leg scattering amplitudes. Inspired by the remarkable properties of the Loop-Tree Duality (LTD), we explain how to reconstruct an integrand level representation of scattering amplitudes which only contains physical singularities. These so-called causal representations can be derived from connected binary partitions of Feynman diagrams, properly entangled according to specific rules. We will focus on the detection of flux orientations which are compatible with causality, describing the implement

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26

"Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method." Tehnicki vjesnik - Technical Gazette 27, no. 2 (2020). http://dx.doi.org/10.17559/tv-20190804140256.

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27

Etminan, Mahyar, Ramin Rezaeianzadeh, and Mohammad A. Mansournia. "Causal diagrams for disease latency bias." International Journal of Epidemiology 53, no. 5 (2024). http://dx.doi.org/10.1093/ije/dyae111.

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Abstract Background Disease latency is defined as the time from disease initiation to disease diagnosis. Disease latency bias (DLB) can arise in epidemiological studies that examine latent outcomes, since the exact timing of the disease inception is unknown and might occur before exposure initiation, potentially leading to bias. Although DLB can affect epidemiological studies that examine different types of chronic disease (e.g. Alzheimer’s disease, cancer etc), the manner by which DLB can introduce bias into these studies has not been previously elucidated. Information on the specific types o

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28

Eichhorn, Astrid, Antonio D. Pereira, and Andreas G. A. Pithis. "The phase diagram of the multi-matrix model with ABAB interaction from functional renormalization." Journal of High Energy Physics 2020, no. 12 (2020). http://dx.doi.org/10.1007/jhep12(2020)131.

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Abstract At criticality, discrete quantum-gravity models are expected to give rise to continuum spacetime. Recent progress has established the functional renormalization group method in the context of such models as a practical tool to study their critical properties and to chart their phase diagrams. Here, we apply these techniques to the multi-matrix model with ABAB interaction potentially relevant for Lorentzian quantum gravity in 3 dimensions. We characterize the fixed-point structure and phase diagram of this model, paving the way for functional RG studies of more general multi-matrix or

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29

Yu, Hui, Wenhao Zhang, and Wei Qu. "A mechanism-driven failure causality modeling approach for mechanical systems combining causal ordering theory and Ishikawa diagram." Scientific Reports 15, no. 1 (2025). https://doi.org/10.1038/s41598-025-12459-9.

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30

Tafti, Ali, and Galit Shmueli. "Causal Inference Grounded in Causal Diagrams: Benefits, Limitations, and Opportunities for the Information Systems Field." MIS Quarterly, 2024. http://dx.doi.org/10.25300/misq/2024/18422.

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We join the important effort of embracing diverse views on causality in a prior Editor’s Comment (Mithas, et al. 2022a). Specifically, we aim to expand the discussion around a major causal framework and toolkit that, we believe, is largely missing and needed in empirical studies in the field of information systems (IS): that of causal diagrams and structural causal modeling (SCM). Being relatively new, the SCM framework has faced resistance from economists that has only recently begun to soften; and for this reason, remains largely absent in econometrics textbooks and in the curriculum of most

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31

Zhu, Yan, Ming Peng, Peng Zhang, and Limin Zhang. "Warning Decision-Making for Landslide Dam Breaching Flood Using Influence Diagrams." Frontiers in Earth Science 9 (August 6, 2021). http://dx.doi.org/10.3389/feart.2021.679862.

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Warning and evacuation are among the most effective ways for saving human lives and properties from landslide dam hazards. A new warning decision model for landslide dam break is developed using Influence Diagrams to minimize the total losses. An Influence Diagram is a simple visual representation of a decision problem. It analyzes the qualitative (causal) relationships between the variables via a logic diagram and determines the quantitative relationships via conditional probability and Bayes’ theorem. The model is applied for the warning decision-making of the 2008 Tangjiashan landslide dam.

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32

Dong, Wei, Shuqing Zhang, Shanshan Song, Xiaowen Zhang, and Xiang Wu. "Refined composite multiscale dynamic causality diagram: a novel time-series analysis approach and its application in fault diagnosis of rotating machinery." Structural Health Monitoring, January 12, 2024. http://dx.doi.org/10.1177/14759217231215351.

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Entropy-based feature extraction methods have been widely used in the fault diagnosis of rotating machinery, but the entropy-based methods still have the defects of poor noise robustness, weak feature extraction, and low computational efficiency. To solve this problem, this article proposes a fault diagnosis method based on refined composite multiscale dynamic causal diagram (RCMSDCD) and local receptive field extreme learning machine (LRFELM). First, a novel feature extraction method, named dynamic causal diagram (DCD), is proposed to comprehensively quantify static and dynamic complexity. DC

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33

Singha, Pracheta, Victor E. Ambruş, and Maxim N. Chernodub. "Inhibition of the splitting of the chiral and deconfinement transition due to rotation in QCD: The phase diagram of the linear sigma model coupled to Polyakov loops." Physical Review D 110, no. 9 (2024). http://dx.doi.org/10.1103/physrevd.110.094053.

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We discuss the effect of rigid rotation on the critical temperatures of deconfinement and chiral transitions in the linear sigma model coupled to quarks and the Polyakov loop. We point out the essential role of the causality condition, which requires that any point of the system should rotate slower than the velocity of light. We show that imposing this physical requirement leads to inhibition of the splitting between the chiral and confining transitions, which becomes negligibly small (ΔT∼1 MeV or less) for experimentally relevant, slow angular velocities Ω∼10 MeV of a (5–10) fm-sized systems

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