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Journal articles on the topic 'Modeling of dynamics'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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1

Kumar, Rakesh, Bharti Saxena, Ritu Shrivastava, and Ramakant Bhardwaj. "Mathematical Modeling of Dengue Disease Transmission Dynamics." Indian Journal Of Science And Technology 17, no. 39 (2024): 4101–10. http://dx.doi.org/10.17485/ijst/v17i39.1526.

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Objectives: This study developed a compartmental ordinary differential equation model to investigate dengue transmission dynamics within a human population. The model stratified the population into susceptible, exposed, infected, and recovered classes, incorporating key epidemiological factors. Methods: Model equilibrium analysis was conducted to determine the stability of disease-free and endemic states. The basic reproduction number (R₀) was calculated to quantify the potential for disease spread. Additionally, sensitivity analysis was performed to assess the impact of key parameters on mode

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2

Malуarets, Lyudmyla M., Anatolii V. Voronin, Irina L. Lebedeva, and Stepan S. Lebediev. "Innovation Development of an Enterprise: Modeling Dynamics." Business Inform 10, no. 549 (2023): 162–74. http://dx.doi.org/10.32983/2222-4459-2023-10-162-174.

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At the present stage of economic development, the leading role in ensuring the competitiveness of both an singular enterprise and the country as a whole, as well as in creating conditions for the transition to sustainable development, is played by the successful implementation of the latest scientific developments in production processes, comprehensive support for the strategy of innovative development. The development and implementation of innovations is a complex dynamic process that requires the use of special research methods. Such a method is system dynamics, which makes it possible to ta

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3

�� and Kirill Zuykov. "Modeling of Project Management Systems Dynamics." Russian Journal of Project Management 2, no. 4 (2013): 25–36. http://dx.doi.org/10.12737/1960.

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Publications on modeling of project management systems dynamics are reviewed. Studies analyzed mainly consider dynamics of project management systems in the organizational environment of projects implementation. History of project management dynamics modeling is presented as well as classification of existing dynamic models. The review includes papers on the following groups of modeling methods: for optimal and sustainable project scheduling, for discrete event simulation and for macro-modeling based on system dynamics. Also analyzed are current trends of modeling methods development in refere

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4

Altonji, Joseph G., Anthony Smith, and Ivan Vidangos. "Modeling Earnings Dynamics." Finance and Economics Discussion Series 2009, no. 08 (2009): 1–74. http://dx.doi.org/10.17016/feds.2009.08.

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5

Davis, Peter. "Modeling communication dynamics." Nonlinear Theory and Its Applications, IEICE 5, no. 2 (2014): 113–26. http://dx.doi.org/10.1587/nolta.5.113.

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6

Vilar, José M. G., Călin C. Guet, and Stanislas Leibler. "Modeling network dynamics." Journal of Cell Biology 161, no. 3 (2003): 471–76. http://dx.doi.org/10.1083/jcb.200301125.

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We use the lac operon in Escherichia coli as a prototype system to illustrate the current state, applicability, and limitations of modeling the dynamics of cellular networks. We integrate three different levels of description (molecular, cellular, and that of cell population) into a single model, which seems to capture many experimental aspects of the system.

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7

Goetz, Michaela, Jure Leskovec, Mary McGlohon, and Christos Faloutsos. "Modeling Blog Dynamics." Proceedings of the International AAAI Conference on Web and Social Media 3, no. 1 (2009): 26–33. http://dx.doi.org/10.1609/icwsm.v3i1.13941.

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How do blogs produce posts? What local, underlying mechanisms lead to the bursty temporal behaviors observed in blog networks? Earlier work analyzed network patterns of blogs and found that blog behavior is bursty and often follows power laws in both topological and temporal characteristics. However, no intuitive and realistic model has yet been introduced, that can lead to such patterns. This is exactly the focus of this work. We propose a generative model that uses simple and intuitive principles for each individual blog, and yet it is able to produce the temporal characteristics of the blog

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8

Charpentier, Arthur, and Marilou Durand. "Modeling earthquake dynamics." Journal of Seismology 19, no. 3 (2015): 721–39. http://dx.doi.org/10.1007/s10950-015-9489-9.

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9

Bindschadler, Mike. "Modeling actin dynamics." Wiley Interdisciplinary Reviews: Systems Biology and Medicine 2, no. 4 (2010): 481–88. http://dx.doi.org/10.1002/wsbm.62.

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10

Mukharlyamov, R. G., and Zh K. Kirgizbaev. "Modeling of dynamics processes and dynamics control." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 114, no. 2 (2024): 165–77. http://dx.doi.org/10.31489/2024m2/165-177.

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Equations and methods of classical mechanics are used to describe the dynamics of technical systems containing elements of various physical nature, planning and management tasks of production and economic objects. The direct use of known dynamics equations with indefinite multipliers leads to an increase in deviations from the constraint equations in the numerical solution. Common methods of constraint stabilization, known from publications, are not always effective. In the general formulation, the problem of constraint stabilization was considered as an inverse problem of dynamics and it requ

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11

Kozmenko, Olha, and Olha Kuzmenko. "Modeling the stability dynamics of Ukrainian banking system." Banks and Bank Systems 8, no. 2 (2013): 55–62. http://dx.doi.org/10.21511/bbs.8(2).2013.01.

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12

Takehara, Shoichiro, Yuichi Kondo, Yoshiaki Terumichi, and Takuya Yoshimura. "64424 MODELING OF TETHERED MOBILITY DEVICE(Aerospace Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _64424–1_—_64424–7_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._64424-1_.

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13

Dew, Ryan, Asim Ansari, and Yang Li. "Modeling Dynamic Heterogeneity Using Gaussian Processes." Journal of Marketing Research 57, no. 1 (2019): 55–77. http://dx.doi.org/10.1177/0022243719874047.

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Marketing research relies on individual-level estimates to understand the rich heterogeneity of consumers, firms, and products. While much of the literature focuses on capturing static cross-sectional heterogeneity, little research has been done on modeling dynamic heterogeneity, or the heterogeneous evolution of individual-level model parameters. In this work, the authors propose a novel framework for capturing the dynamics of heterogeneity, using individual-level, latent, Bayesian nonparametric Gaussian processes. Similar to standard heterogeneity specifications, this Gaussian process dynami

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14

Sani, Kartono, Manahan Siallagan, Utomo Sarjono Putro, and Kuntoro Mangkusubroto. "Policy Development for the Energy Mix in Indonesia Using System Dynamics." GATR Global Journal of Business and Social Science Review (GJBSSR) Vol.5(3) Jul-Sep 2017 5, no. 3 (2017): 137–58. http://dx.doi.org/10.35609/gjbssr.2017.5.3(16).

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Objective - This paper discusses a literature review regarding finding system dynamics modeling as the preferred approach to building the national energy system model in Indonesia and introduces the uniqueness of the initial system dynamics model of the Indonesia energy mix today. Methodology/Technique - A literature review about system modeling of energy portfolio management worldwide to find the research gaps and to screen for the preferred modeling approach for the country. Along with past statistics in the background, a combination of system dynamics modeling and focus group discussion is

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15

Tang, Liang, Yi Zhang, and Hua Deng. "Dynamic Modeling and Analysis of Underactuated Prosthetic Hand." Advanced Materials Research 655-657 (January 2013): 400–407. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.400.

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Based on the kinematic equation of index finger, the trajectory space of fingertip is analyzed, and the structural parameters of underactuated prosthetic hand have been optimized by ADAMS, which compare the trajectory space with the index-finger. Using the modeling methods of Lagrange dynamics equation, the dynamic model is established for the three-joint underactuated prosthetic finger, whose kinematic and dynamic characteristics also are analyzed. Finally, by the construction of the virtual prototype and its introduction into ADAMS for the dynamics simulation, the correctness of kinematics a

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16

Jiao, Bohan, and Zhaohui Dang. "Nonlinear Dynamics Model of DFACS with Two Test Masses for Heliocentric Space Gravitational Wave Detection Mission." Advances in Computer and Materials Scienc Research 2, no. 1 (2025): 240. https://doi.org/10.70114/acmsr.2025.2.1.p240.

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This paper conducts a comprehensive study on the nonlinear dynamic modeling of the two test masses Drag-Free and Attitude Control System (DFACS) for heliocentric gravitational wave detection missions. First, the composition of DFACS and the modeling assumptions are clarified, key reference frames and their transformation relationships are defined, and an innovative modeling approach based on the formation reference frame is proposed to characterize the geometric constraints among multiple DFACSs. Subsequently, a systemic nonlinear dynamic model is established, encompassing spacecraft relative

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17

Milić Beran, Ivona. "SYSTEM-DYNAMIC MODELING OF THE IMPACT OF SOCIAL CAPITAL ON ECONOMIC GROWTH." DIEM: Dubrovnik International Economic Meeting 6, no. 1 (2021): 25–32. http://dx.doi.org/10.17818/diem/2021/1.3.

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This paper presents a qualitative and quantitative system-dynamic modeling of the impact of social capital on economic growth. Social capital is the most problematic of all the concepts that determine progress. On a broad conceptual level, there is agreement about the importance of social capital, which has been used to explain differences in progress among nations with similar natural, human and physical capital. Recent research suggests that it is more important to include an explanation of the interaction of economic actors and their organization when measuring progress than to measure prog

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18

Caux, S., and R. Zapata. "Modeling and control of biped robot dynamics." Robotica 17, no. 4 (1999): 413–26. http://dx.doi.org/10.1017/s0263574799001411.

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This paper addresses the problem of modeling biped dynamics and the use of such models for the control of walking, running and jumping robots. We describe two approaches to dynamic modeling: the basic Lagrange approach and the non-regular dynamic approach. The new non-regular dynamic approach takes into account discontinuities due to rigid contact between punctual feet and the ground without computing the exact impact time. The contact is close to the physical situation given by non-linear laws (impenetrability, non-smooth contact and real friction cone). Contact dynamics can be well managed w

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19

Mukherjee, Saikat, Dmitry A. Fedorov, and Sergey A. Varganov. "Modeling Spin-Crossover Dynamics." Annual Review of Physical Chemistry 72, no. 1 (2021): 515–40. http://dx.doi.org/10.1146/annurev-physchem-101419-012625.

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In this article, we review nonadiabatic molecular dynamics (NAMD) methods for modeling spin-crossover transitions. First, we discuss different representations of electronic states employed in the grid-based and direct NAMD simulations. The nature of interstate couplings in different representations is highlighted, with the main focus on nonadiabatic and spin-orbit couplings. Second, we describe three NAMD methods that have been used to simulate spin-crossover dynamics, including trajectory surface hopping, ab initio multiple spawning, and multiconfiguration time-dependent Hartree. Some aspects

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20

Costanza, Robert, Fred H. Sklar, and Mary L. White. "Modeling Coastal Landscape Dynamics." BioScience 40, no. 2 (1990): 91–107. http://dx.doi.org/10.2307/1311342.

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21

Malkov, Sergey Yu. "World dynamics patterns modeling." Computer Research and Modeling 9, no. 3 (2017): 419–32. http://dx.doi.org/10.20537/2076-7633-2017-9-3-419-432.

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22

A. Peletier, Lambertus. "Modeling drug-protein dynamics." Discrete & Continuous Dynamical Systems - S 5, no. 1 (2012): 191–207. http://dx.doi.org/10.3934/dcdss.2012.5.191.

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23

Mahon, John F., and Richard A. McGowan. "Modeling Industry Political Dynamics." Business & Society 37, no. 4 (1998): 390–413. http://dx.doi.org/10.1177/000765039803700404.

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24

Charlebois, Daniel A., and Gábor Balázsi. "Modeling cell population dynamics." In Silico Biology 13, no. 1-2 (2019): 21–39. http://dx.doi.org/10.3233/isb-180470.

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25

Cobey, Sarah. "Modeling infectious disease dynamics." Science 368, no. 6492 (2020): 713–14. http://dx.doi.org/10.1126/science.abb5659.

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26

GAO, Jinhua, Yue LIU, and Xueqi CHENG. "Decentralized cascade dynamics modeling." SCIENTIA SINICA Informationis 48, no. 11 (2018): 1575–88. http://dx.doi.org/10.1360/n112018-00081.

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27

Alderton, Gemma. "Modeling infectious disease dynamics." Science 368, no. 6492 (2020): 726.9–728. http://dx.doi.org/10.1126/science.368.6492.726-i.

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28

Rosselló, Jaume, Eugeni Aguiló, and Antoni Riera. "Modeling Tourism Demand Dynamics." Journal of Travel Research 44, no. 1 (2005): 111–16. http://dx.doi.org/10.1177/0047287505276602.

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29

D'Innocenzo, A., and L. Renna. "Modeling leaky faucet dynamics." Physical Review E 55, no. 6 (1997): 6776–90. http://dx.doi.org/10.1103/physreve.55.6776.

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30

Hallam, Thomas G., Ray R. Lassiter, and Shandelle M. Henson. "Modeling fish population dynamics." Nonlinear Analysis: Theory, Methods & Applications 40, no. 1-8 (2000): 227–50. http://dx.doi.org/10.1016/s0362-546x(00)85013-0.

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31

Teodorescu, Horia-Nicolai, Abraham Kandel, and Moti Schneider. "Fuzzy modeling and dynamics." Fuzzy Sets and Systems 106, no. 1 (1999): 1–2. http://dx.doi.org/10.1016/s0165-0114(98)00352-2.

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32

Whitby, Evan R., and Peter H. McMurry. "Modal Aerosol Dynamics Modeling." Aerosol Science and Technology 27, no. 6 (1997): 673–88. http://dx.doi.org/10.1080/02786829708965504.

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33

Nadrowski, Björn, and Martin C. Göpfert. "Modeling auditory transducer dynamics." Current Opinion in Otolaryngology & Head and Neck Surgery 17, no. 5 (2009): 400–406. http://dx.doi.org/10.1097/moo.0b013e3283303443.

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34

Chenney, S., J. Ichnowski, and D. Forsyth. "Dynamics modeling and culling." IEEE Computer Graphics and Applications 19, no. 2 (1999): 79–87. http://dx.doi.org/10.1109/38.749126.

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35

Batzer, Stephen A., Alexander M. Gouskov, and Sergey A. Voronov. "Modeling Vibratory Drilling Dynamics." Journal of Vibration and Acoustics 123, no. 4 (2001): 435–43. http://dx.doi.org/10.1115/1.1387024.

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The dynamic behavior of deep-hole vibratory drilling is analyzed. The mathematical model presented allows the determination of axial tool and workpiece displacements and cutting forces for significant dynamic system behavior such as the engagement and disengagement of the cutting tool into the workpiece material and tool breakthrough. Model parameters include the actual rigidity of the tool and workpiece holders, time-varying chip thickness, time lag for chip formation due to tool rotation and possible disengagement of drill cutting edges from the workpiece due to tool and/or workpiece axial v

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36

Brandt, Patrick T., and John R. Freeman. "Modeling Macro-Political Dynamics." Political Analysis 17, no. 2 (2009): 113–42. http://dx.doi.org/10.1093/pan/mpp001.

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Analyzing macro-political processes is complicated by four interrelated problems: model scale, endogeneity, persistence, and specification uncertainty. These problems are endemic in the study of political economy, public opinion, international relations, and other kinds of macro-political research. We show how a Bayesian structural time series approach addresses them. Our illustration is a structurally identified, nine-equation model of the U.S. political-economic system. It combines key features of the model of Erikson, MacKuen, and Stimson (2002) of the American macropolity with those of a l

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37

Haddadi, Hamed, Steve Uhlig, Andrew Moore, Richard Mortier, and Miguel Rio. "Modeling internet topology dynamics." ACM SIGCOMM Computer Communication Review 38, no. 2 (2008): 65–68. http://dx.doi.org/10.1145/1355734.1355745.

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38

Kim, Chul, P. K. Kannan, Michael Trusov, and Andrea Ordanini. "Modeling Dynamics in Crowdfunding." Marketing Science 39, no. 2 (2020): 339–65. http://dx.doi.org/10.1287/mksc.2019.1209.

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39

Hadley, David M., Victor F. Froelicher, and Paul J. Wang. "QT dynamics—modeling hysteresis." Journal of Electrocardiology 43, no. 6 (2010): 642. http://dx.doi.org/10.1016/j.jelectrocard.2010.10.007.

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40

Valera, Oliver. "Modeling para oscillatory dynamics." Biophysical Journal 123, no. 3 (2024): 413a. http://dx.doi.org/10.1016/j.bpj.2023.11.2522.

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41

Tolkachev, Akim. "Modeling and control of a chaotic process." Modeling of systems and processes 15, no. 4 (2022): 128–36. http://dx.doi.org/10.12737/2219-0767-2022-15-4-128-136.

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The article investigates problems related to the control of the dynamics of a system given by the Henon map with a hysteresis component included in it. In particular, possible modifications of the limit set (attractor) of the modified Henon map under hysteresis conditions are studied. The hysteresis element is formalized based on design approach by means of the Preisach model, which is approximated by a system consisting of a finite set of non-ideal relays. To analyze the dynamics, numerical simulation is carried out for various values of the model parameters, which are characterized by chaoti

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42

Martínez-Marín, Sindy, Nataly Puello-Pereira, and David Ovallos-Gazabon. "Cluster Competitiveness Modeling: An Approach with Systems Dynamics." Social Sciences 9, no. 2 (2020): 12. http://dx.doi.org/10.3390/socsci9020012.

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This study makes a systemic review to cluster and create a competitiveness relationship considering a systems dynamics approach. A dynamic hypothesis was constructed to validate what factors increase a cluster’s level of competitiveness, through causal analysis. Then, the causal diagram that validates the dynamic H0 hypothesis was constructed in Vensim PLE systems®. Literature review shows the evolution of the cluster system according to the current needs of the market, and emphasizes the need for new approaches and models that capture the complexity and dynamics of this system, allowing the u

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43

Mills, J. K., and C. V. Nguyen. "Robotic Manipulator Collisions: Modeling and Simulation." Journal of Dynamic Systems, Measurement, and Control 114, no. 4 (1992): 650–59. http://dx.doi.org/10.1115/1.2897737.

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In this paper, a new formulation of the dynamics of a robotic manipulator work environment is presented. The work environment is modeled in a way that permits the robot transition to and from contact with the work environment to be effectively simulated. This method circumvents the discontinuities inherent in previously proposed models of work environment dynamic models that have, until now, prevented researchers from considering that phase of manipulation. Combined with an existing model of the manipulator dynamics, the overall model of the manipulator-work environment system is such that the

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44

MANDELJ, SIMON, IGOR GRABEC, and EDVARD GOVEKAR. "STATISTICAL APPROACH TO MODELING OF SPATIOTEMPORAL DYNAMICS." International Journal of Bifurcation and Chaos 11, no. 11 (2001): 2731–38. http://dx.doi.org/10.1142/s0218127401003802.

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Often in the analysis of spatially extended dynamic systems, we do not know an analytical model of the system dynamics, but we can provide spatiotemporal records of the characteristic state variable. The question then arises of how to extract a model of the system dynamics from the corresponding data. As a quite general solution of this problem, we propose a nonparametric statistical method of local modeling. The performance of the proposed method is demonstrated by predicting typical examples of spatiotemporal chaotic data. The results of modeling indicate that the statistical method can be a

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45

Ma, Chang Lin, Feng Li, Yong Bao Feng, and Xiao Guang Yao. "The Study on Dynamic Modeling of Complex Mechanism Based on Multi Software Collaboration." Advanced Materials Research 945-949 (June 2014): 87–90. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.87.

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At present, the accurate dynamic modeling and simulation of complex movement mechanism using a single software is a difficult problem. The paper proposes the "collaborative simulation run" method of multi-domain model based on the interfaces of multi simulation software, and it can achieve the design and analysis of complex mechanism system. Selecting the 3D modeling software Pro/E, the dynamics analysis software ADAMS and finite element analysis software ANSYS as a collaborative modeling analysis platform, the transmission relationship between software data interfaces is studied, and the rigi

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46

Yang, Jian Xin, Zhen Tao Liu, and Jian Wei Sun. "Dynamic Modeling of Overconstrained Parallel Robot." Applied Mechanics and Materials 373-375 (August 2013): 34–37. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.34.

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The dynamic modeling method for parallel robot based on the principle of virtual work and equivalent tree structure is proposed by taking off the platform and the chains as well as degenerating parallel robot into a tree structure, the closed-form solutions for the inverse and forward dynamics models of parallel robot are derived. The method is applied on kinematics and dynamics analysis of a representative 3-RRR spherical parallel robot.

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47

Cho, D., and J. K. Hedrick. "Automotive Powertrain Modeling for Control." Journal of Dynamic Systems, Measurement, and Control 111, no. 4 (1989): 568–76. http://dx.doi.org/10.1115/1.3153093.

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A dynamic model of an automotive powertrain system is developed by the use of eight states and two time-delays in the continuous-time domain, with careful attention given to the dynamics and kinematics of a four-stroke spark-ignition engine, an automatic transmission, and rubber tires. The model is relatively simple, yet it predicts the important dynamics (including those during a shift) quite well when compared to experimental data. The model is well suited for developing powertrain controllers and can also be used for studying the dynamic behavior of a powertrain system. A great deal of effo

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48

Sun, Ao, and Ting Qiang Yao. "Modeling and Analysis of Planar Multibody System Containing Deep Groove Ball Bearing with Slider-Crank Mechanism." Advanced Materials Research 753-755 (August 2013): 918–23. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.918.

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With the rotating machinery system developing toward high speed, high precision, and high reliability direction, ball bearing dynamic performance have a critical impact to dynamics characteristics of support system. Based on multibody dynamics theory and contact dynamics method,and considering the ball and ring raceway 3 d dynamic contact relationship, using ADAMS dynamics analysis software to establish the multibody dynamics model of crank slider mechanism containing ball bearing dynamic contact relationship.The simulation analysis of the dynamic performance of the ball bearing and the crank

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49

Gulati, Navneet, and Eric J. Barth. "Dynamic Modeling of a Monopropellant-Based Chemofluidic Actuation System." Journal of Dynamic Systems, Measurement, and Control 129, no. 4 (2006): 435–45. http://dx.doi.org/10.1115/1.2718243.

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This paper presents a dynamic model of a monopropellant-based chemofluidic power supply and actuation system. The proposed power supply and actuation system, as presented in prior works, is motivated by the current lack of a viable system that can provide adequate energetic autonomy to human-scale power-comparable untethered robotic systems. As such, the dynamic modeling presented herein is from an energetic standpoint by considering the power and energy exchanged and stored in the basic constituents of the system. Two design configurations of the actuation system are presented and both are mo

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50

Aylaj, Bouchra, Nicola Bellomo, Livio Gibelli, and Damián Knopoff. "Crowd Dynamics by Kinetic Theory Modeling: Complexity, Modeling,." Synthesis Lectures on Mathematics and Statistics 12, no. 4 (2020): 1–98. http://dx.doi.org/10.2200/s01055ed1v01y202009mas036.

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