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Journal articles on the topic 'Dynamic Systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Bakal, Chris. "Dynamic systems." Genome Biology 13, no. 1 (2012): 312. http://dx.doi.org/10.1186/gb-2012-13-1-312.

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2

Sharif, Amir M. "Can systems dynamics be effective in modelling dynamic business systems?" Business Process Management Journal 11, no. 5 (2005): 612–15. http://dx.doi.org/10.1108/14637150510619911.

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3

Sachs, K., S. Itani, J. Fitzgerald, B. Schoeberl, G. P. Nolan, and C. J. Tomlin. "Single timepoint models of dynamic systems." Interface Focus 3, no. 4 (2013): 20130019. http://dx.doi.org/10.1098/rsfs.2013.0019.

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Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We en

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4

Osipov, G. S. "Intelligent dynamic systems." Scientific and Technical Information Processing 37, no. 5 (2010): 259–64. http://dx.doi.org/10.3103/s0147688210050023.

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5

Tanaka, D. L., J. M. Krupinsky, M. A. Liebig, et al. "Dynamic Cropping Systems." Agronomy Journal 94, no. 5 (2002): 957–61. http://dx.doi.org/10.2134/agronj2002.9570.

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6

Power, Mary E. "Engaging Dynamic Systems." BioScience 57, no. 8 (2007): 707–9. http://dx.doi.org/10.1641/b570812.

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7

Haykin, Simon. "Cognitive Dynamic Systems." International Journal of Cognitive Informatics and Natural Intelligence 5, no. 4 (2011): 33–43. http://dx.doi.org/10.4018/jcini.2011100103.

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The main topics covered in this paper address the following four issues: 1) Distinction between how adaptation and cognition are viewed with respect to each other, 2) With human cognition viewed as the framework for cognition, the following cognitive processes are identified: the perception-action cycle, memory, attention, intelligence, and language. With language being outside the scope of the paper, detailed accounts of the other four cognitive processes are discussed, 3) Cognitive radar is singled out as an example application of cognitive dynamic systems that “mimics” the visual brain; exp

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8

Haykin, Simon. "Cognitive Dynamic Systems." Proceedings of the IEEE 94, no. 11 (2006): 1910–11. http://dx.doi.org/10.1109/jproc.2006.886014.

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9

Veitch, James, and Robert Laddaga. "Distributed dynamic systems." Communications of the ACM 41, no. 5 (1998): 34–36. http://dx.doi.org/10.1145/274946.274953.

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10

Schwartz, Daniel G. "Dynamic Reasoning Systems." ACM Transactions on Computational Logic 16, no. 4 (2015): 1–42. http://dx.doi.org/10.1145/2798727.

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11

Kamenskii, G. A. "Smoothing dynamic systems." Nonlinear Analysis: Theory, Methods & Applications 27, no. 10 (1996): 1117–24. http://dx.doi.org/10.1016/0362-546x(95)00123-d.

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12

Tanaka, D. L., J. M. Krupinsky, M. A. Liebig, et al. "Dynamic Cropping Systems." Agronomy Journal 94, no. 5 (2002): 957. http://dx.doi.org/10.2134/agronj2002.0957.

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13

Stefanuk, V. L. "Dynamic expert systems." Kybernetes 29, no. 5/6 (2000): 702–9. http://dx.doi.org/10.1108/03684920010333134.

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14

Barboiu, Mihail, and Jean‐Marie Lehn. "Constitutional Dynamic Systems." Israel Journal of Chemistry 53, no. 1‐2 (2013): 9–10. http://dx.doi.org/10.1002/ijch.201310003.

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15

SZATKOWSKI, ANDRZEJ. "Generalized dynamical systems: differentiable dynamic complexes and differential dynamic systems." International Journal of Systems Science 21, no. 8 (1990): 1631–57. http://dx.doi.org/10.1080/00207729008910481.

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16

Panova, Yulia, and Olli-Pekka Hilmola. "DYNAMIC BOTTLENECKS IN HANDLING AND STORAGE SYSTEMS." Russian Journal of Logistics and Transport Management 2, no. 1 (2015): 11–19. http://dx.doi.org/10.20295/2313-7002-2015-1-11-19.

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17

Sapaty, P. S. "Spatial grasp model for dynamic distributed systems." Mathematical machines and systems 3 (2021): 3–21. http://dx.doi.org/10.34121/1028-9763-2021-3-21.

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More complex distributed and intelligent systems which relate to economy, ecology, communi-cations, security and defense, and cover both terrestrial and celestial environments are being developed. Their efficient management, especially in dynamic and unpredictable situations, needs serious investigations and development in scientific and technological areas. Their tradi-tional representations as parts operating by certain algorithms and exchanging messages are be-coming inadequate as such systems need much stronger integration to operate as holistic organ-isms pursuing global and often varying

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18

Charles Hyland, David. "Intensity Correlation Imaging and Nonnegative Dynamic Systems." Annals of Computational Physics and Material Science 2, no. 1 (2025): 01–07. https://doi.org/10.33140/acpms.02.01.03.

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This work is a supplement to the author’s sequence of three papers featured in Applied Optics and listed in the Reference section. The main contribution of the author’s algorithm was the survey of the stochastic search algorithm required to determine the true noise-free image via the Brown-Twiss effect with enormously small integration times. A key element in the algorithm was the introduction of initial conditions where the values of the intensity pixels are assumed to be mutually statistically independent and uniformly distributed over the range [0, δ] where δ there is a (very small) positiv

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19

Nicolis, G., and C. Nicolis. "Nonlinear dynamic systems in the geosciences." Bulletin (Kansas Geological Survey), no. 233 (April 16, 2024): 33–42. https://doi.org/10.17161/kgsbulletin.no.233.20447.

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Geophysical phenomena are often characterized by complex, random-looking deviations of the relevant variables from their average values. Typical examples of such aperiodicity are the intermittent succession of Quaternary glaciations as revealed by the oxygen isotope record of deep-sea cores of the last 106 years or the pronounced spatial disorder characterizing geologic materials. A major task of the geoscientist is to reconstitute from this type of record the principal mechanisms responsible for the observed behavior. Traditional approaches attribute the complexity encountered in the record o

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20

de la Sen, M., J. L. Malo, and M. J. Gonzalez-Gomez. "Energy Balances in Dynamic Systems Under Unmodelled Dynamics." IFAC Proceedings Volumes 22, no. 18 (1989): 65–70. http://dx.doi.org/10.1016/s1474-6670(17)52822-0.

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21

Rodríguez Velásquez, Javier Oswaldo, Jaime Alberto Páez Páez, Sandra Catalina Correa Herrera, et al. "Software for adult cardiac dynamic through dynamic systems." Visión electrónica 13, no. 1 (2019): 50–56. http://dx.doi.org/10.14483/22484728.14440.

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The normal and abnormal behavior of an adult heart dynamics and its state of evolution towards one of these two states has been characterized successfully in the context of the theory of dynamic systems and probability. The diagnostic methodology of clinical application designed under these two theories has managed to evaluate in an objective and reproducible way the cardiac dynamics from the values of the frequency of the Holter registers. The automation of this methodology through the design of a software that can be docked in any operating system for PC, and contributes as a diagnostic aid

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22

Iqbal, N., J. Buisson, and Y. Quenec'hdu. "Stability of Dynamic Hybrid Systems With Descriptor Systems as Dynamic Model." IFAC Proceedings Volumes 30, no. 6 (1997): 361–67. http://dx.doi.org/10.1016/s1474-6670(17)43391-x.

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23

Górecki, H., and M. Zaczyk. "Extremal dynamic errors in linear dynamic systems." Bulletin of the Polish Academy of Sciences: Technical Sciences 58, no. 1 (2010): 99–105. http://dx.doi.org/10.2478/v10175-010-0010-x.

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Extremal dynamic errors in linear dynamic systems Two different analytical methods of determining extremal dynamic errors in linear dynamic systems are presented. The main idea of these methods is based on finding certain additional equations. These additional equations are obtained due to the assumption that an extremal point τ obtained from the necessary condition , is also an extremum point with respect to initial conditions, that is, .

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24

Barraza, Manuel, Fernando Matía, and Basil Mohammed Al-Hadithi. "Dynamic Analysis of Fuzzy Systems." Applied Sciences 13, no. 3 (2023): 1934. http://dx.doi.org/10.3390/app13031934.

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In this work, a new methodology for the dynamic analysis of non-linear systems is developed by applying the Mamdani fuzzy model. With this model, parameters such as settling time, peak time and overshoot will be obtained. The dynamic analysis of non-linear fuzzy systems with triangular membership functions is performed, and linguistic variables describing overly complex or ill-defined phenomena are used to fit the model. Scaling factors will simplify the modification of the variables, making them easier to find the system model. The specifications of second-order characteristics in the time do

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25

Verlan, A., and Jo Sterten. "Methods of Complex Dynamic Systems’ Models’ Equivalent Conversion." Mathematical and computer modelling. Series: Technical sciences 1, no. 20 (2019): 16–25. http://dx.doi.org/10.32626/2308-5916.2019-20.16-25.

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26

Korolyov, Alexander, and Huiyu Zhou. "Dynamic damper pressure fluctuation in the pumping systems." Odes’kyi Politechnichnyi Universytet. Pratsi, no. 1 (April 27, 2016): 50–60. http://dx.doi.org/10.15276/opu.1.48.2016.07.

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27

Popkov, Y. S. "Oscillations in Dynamic Systems with an Entropy Operator." Nelineinaya Dinamika 19, no. 1 (2023): 0. http://dx.doi.org/10.20537/nd230101.

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This paper considers dynamic systems with an entropy operator described by a perturbed constrained optimization problem. Oscillatory processes are studied for periodic systems with the following property: the entire system has the same period as the process generated by its linear part. Existence and uniqueness conditions are established for such oscillatory processes, and a method is developed to determine their form and parameters. Also, the general case of noncoincident periods is analyzed, and a method is proposed to determine the form, parameters, and the period of such oscillations. Almo

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28

Awrejcewicz, Jan, and José A. Tenreiro Machado. "Entropy in Dynamic Systems." Entropy 21, no. 9 (2019): 896. http://dx.doi.org/10.3390/e21090896.

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In order to measure and quantify the complex behavior of real-world systems, either novel mathematical approaches or modifications of classical ones are required to precisely predict, monitor and control complicated chaotic and stochastic processes [...]

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29

Sabry, Khaled, and Jeff Barker. "Dynamic Interactive Learning Systems." Innovations in Education and Teaching International 46, no. 2 (2009): 185–97. http://dx.doi.org/10.1080/14703290902843836.

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30

Collings, Patti B. "Fathom: Dynamic Systems Software." American Statistician 55, no. 3 (2001): 258–59. http://dx.doi.org/10.1198/tas.2001.s123.

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31

Rabbath, C. A., M. Abdoune, J. Belanger, and K. Butts. "Simulating hybrid dynamic systems." IEEE Robotics & Automation Magazine 9, no. 2 (2002): 39–47. http://dx.doi.org/10.1109/mra.2002.1019489.

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32

Thelen, Esther. "Dynamic Systems for Everyone." Contemporary Psychology: A Journal of Reviews 41, no. 10 (1996): 1002–3. http://dx.doi.org/10.1037/004523.

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33

Chacon, Edgar, Gisela De Sarrazin, and Ferenc Szigeti. "Pseudo dynamic hybrid systems." Nonlinear Analysis: Theory, Methods & Applications 30, no. 4 (1997): 2533–37. http://dx.doi.org/10.1016/s0362-546x(96)00143-5.

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34

Russell, David W. "Dynamic Systems & Chaos." IFAC Proceedings Volumes 31, no. 29 (1998): 6. http://dx.doi.org/10.1016/s1474-6670(17)38316-7.

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35

Satake, Akiharu, and Yoshiaki Kobuke. "Dynamic supramolecular porphyrin systems." Tetrahedron 61, no. 1 (2005): 13–41. http://dx.doi.org/10.1016/j.tet.2004.10.073.

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36

Leman, M. "Music and dynamic systems." Interface 19, no. 1 (1990): 1. http://dx.doi.org/10.1080/09298219008570552.

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37

Martin, Clyde, K. P. Loucks, and Bijoy K. Ghosh. "Homogeneous dynamic systems theory." IFAC Proceedings Volumes 32, no. 2 (1999): 1410–15. http://dx.doi.org/10.1016/s1474-6670(17)56239-4.

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38

Polyakov, N. L., and M. V. Shamolin. "On Dynamic Aggregation Systems." Journal of Mathematical Sciences 244, no. 2 (2019): 278–93. http://dx.doi.org/10.1007/s10958-019-04619-w.

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39

Albeverio, S., A. Khrennikov, B. Tirozzi, and S. De Smedt. "p-adic dynamic systems." Theoretical and Mathematical Physics 114, no. 3 (1998): 276–87. http://dx.doi.org/10.1007/bf02575441.

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40

Dumortier, Ir Frits. "Control and dynamic systems." Automatica 28, no. 3 (1992): 650–52. http://dx.doi.org/10.1016/0005-1098(92)90194-k.

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41

Štecha, J. "Modeling of dynamic systems." Automatica 32, no. 6 (1996): 946–47. http://dx.doi.org/10.1016/0005-1098(96)89429-5.

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42

Popescu, Theodor D. "Modeling of dynamic systems." Control Engineering Practice 3, no. 6 (1995): 897–98. http://dx.doi.org/10.1016/0967-0661(95)90022-5.

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43

Charbonnier, F., H. Alla, and R. David. "Discrete-event dynamic systems." IEEE Transactions on Control Systems Technology 7, no. 2 (1999): 175–87. http://dx.doi.org/10.1109/87.748144.

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44

Hide, R. "Chaos in Dynamic Systems." Physics Bulletin 37, no. 9 (1986): 390. http://dx.doi.org/10.1088/0031-9112/37/9/034.

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45

Ligęza, Antoni. "Dynamic backward reasoning systems." Artificial Intelligence 43, no. 2 (1990): 127–52. http://dx.doi.org/10.1016/0004-3702(90)90083-c.

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46

Heitmann, Stewart, and Michael Breakspear. "Putting the “dynamic” back into dynamic functional connectivity." Network Neuroscience 2, no. 2 (2018): 150–74. http://dx.doi.org/10.1162/netn_a_00041.

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The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term “dynamic functional connectivity” implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional) connectivity that arise in dynamical systems with two or more subsystems; general

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47

Adler, Rasmus, Frank Elberzhager, Rodrigo Falcão, and Julien Siebert. "Defining and Researching “Dynamic Systems of Systems”." Software 3, no. 2 (2024): 183–205. http://dx.doi.org/10.3390/software3020009.

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Digital transformation is advancing across industries, enabling products, processes, and business models that change the way we communicate, interact, and live. It radically influences the evolution of existing systems of systems (SoSs), such as mobility systems, production systems, energy systems, or cities, that have grown over a long time. In this article, we discuss what this means for the future of software engineering based on the results of a research project called DynaSoS. We present the data collection methods we applied, including interviews, a literature review, and workshops. As o

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48

Zahariev, E. V. "Earthquake dynamic response of large flexible multibody systems." Mechanical Sciences 4, no. 1 (2013): 131–37. http://dx.doi.org/10.5194/ms-4-131-2013.

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Abstract. In the paper dynamics of large flexible structures imposed on earthquakes and high amplitude vibrations is regarded. Precise dynamic equations of flexible systems are the basis for reliable motion simulation and analysis of loading of the design scheme elements. Generalized Newton–Euler dynamic equations for rigid and flexible bodies are applied. The basement compulsory motion realized because of earthquake or wave propagation is presented in the dynamic equations as reonomic constraints. The dynamic equations, algebraic equations and reonomic constraints compile a system of differen

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49

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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50

Pervin, Lawrence A. "A Dynamic Systems Approach to Personality." European Psychologist 6, no. 3 (2001): 172–76. http://dx.doi.org/10.1027//1016-9040.6.3.172.

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David Magnusson has been the most articulate spokesperson for a holistic, systems approach to personality. This paper considers three concepts relevant to a dynamic systems approach to personality: dynamics, systems, and levels. Some of the history of a dynamic view is traced, leading to an emphasis on the need for stressing the interplay among goals. Concepts such as multidetermination, equipotentiality, and equifinality are shown to be important aspects of a systems approach. Finally, attention is drawn to the question of levels of description, analysis, and explanation in a theory of person

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