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Статті в журналах з теми "Modeling Complex Systems"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 30 січня 2023

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1

Xepapadeas, Anastasios. "Modeling complex systems." Agricultural Economics 41 (November 2010): 181–91. http://dx.doi.org/10.1111/j.1574-0862.2010.00499.x.

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2

Schreckenberg, M. "Modeling Complex Systems." Journal of Physics A: Mathematical and General 37, no. 40 (September 23, 2004): 9603. http://dx.doi.org/10.1088/0305-4470/37/40/b01.

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3

Costanza, Robert, Lisa Wainger, and Carl Folke. "Modeling Complex Ecological Economic Systems." BioScience 43, no. 8 (September 1993): 545–55. http://dx.doi.org/10.2307/1311949.

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4

Kondratiev, Y. "Stochastic modeling of complex systems." Мiждисциплiнарнi дослiдження складних систем, no. 1 (2012): 9–13. http://dx.doi.org/10.31392/2307-4515/2012-1.1.

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5

Mirchandani, Chandru. "Resilience Modeling in Complex Systems." Procedia Computer Science 168 (2020): 232–40. http://dx.doi.org/10.1016/j.procs.2020.02.262.

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6

Rachdi, Nabil, Jean-Claude Fort, Thierry Klein, and Fabien Mangeant. "Modeling uncertainties in complex systems." Procedia - Social and Behavioral Sciences 2, no. 6 (2010): 7728–29. http://dx.doi.org/10.1016/j.sbspro.2010.05.200.

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7

Makowski, Marek, Yoshiteru Nakamori, and Hans-Jürgen Sebastian. "Advances in complex systems modeling." European Journal of Operational Research 166, no. 3 (November 2005): 593–96. http://dx.doi.org/10.1016/j.ejor.2004.07.001.

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8

Shlesinger, Michael F. "Book Review: Modeling Complex Systems." Journal of Statistical Physics 119, no. 3-4 (May 2005): 949–50. http://dx.doi.org/10.1007/s10955-004-2132-8.

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9

Filev, Dimiter. "Fuzzy modeling of complex systems." International Journal of Approximate Reasoning 5, no. 3 (May 1991): 281–90. http://dx.doi.org/10.1016/0888-613x(91)90013-c.

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10

Weisbuch, Gérard. "Modeling complex systems: Do it!" Complexity 11, no. 3 (January 2006): 25–26. http://dx.doi.org/10.1002/cplx.20113.

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11

Upchurch, E. T., K. S. Raman, and K. Ranai. "Designing expert systems for modeling complex computer systems." ISA Transactions 28, no. 1 (January 1989): 27–29. http://dx.doi.org/10.1016/0019-0578(89)90053-0.

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12

Gerget, Ol'ga, and Vladimir Kochegurov. "Mathematical modeling of complex homeostatic systems." Science Bulletin of the Novosibirsk State Technical University, no. 4 (December 20, 2014): 89–94. http://dx.doi.org/10.17212/1814-1196-2014-4-89-94.

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13

LESSER, MARTIN. "NONLINEAR MODELING OF COMPLEX MECHANICAL SYSTEMS." International Journal of Bifurcation and Chaos 04, no. 03 (June 1994): 521–51. http://dx.doi.org/10.1142/s0218127494000381.

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Анотація:

This article provides an introduction to a technique for formulating nonlinear models of mechanical systems composed of interconnected and constrained rigid body systems such as those encountered in vehicle technology, biomechanics, spacecraft design and robotics. The approach is based on an algorithm developed by Kane to treat nonholonomic systems, for example systems with rolling constraints. The algorithm is interpreted geometrically in terms of tangent vectors to the instantaneous configuration manifold embedded in the space of nonconstrained motions for the system. The level and style of the presentation is intended to be understood by scientifically literate readers with minimal knowledge in mechanics beyond the introductory level. Examples also show how computer algebra can be used to reduce the effort required for treating complex systems. An annotated reference list, which includes a discussion of computer software, is also provided.

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14

Marsili, Matteo, Iacopo Mastromatteo, and Yasser Roudi. "On sampling and modeling complex systems." Journal of Statistical Mechanics: Theory and Experiment 2013, no. 09 (September 6, 2013): P09003. http://dx.doi.org/10.1088/1742-5468/2013/09/p09003.

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15

lyengar, S. Sitharama. "Computer Modeling of Complex Biological Systems." Journal of Clinical Engineering 13, no. 2 (March 1988): 79–97. http://dx.doi.org/10.1097/00004669-198803000-00004.

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16

Warwick, Walter, Laura Marusich, and Norbou Buchler. "Complex Systems And Human Performance Modeling." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57, no. 1 (September 2013): 803–7. http://dx.doi.org/10.1177/1541931213571175.

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17

Voit, E., Z. Qi, and G. Miller. "Steps of Modeling Complex Biological Systems." Pharmacopsychiatry 41, S 01 (September 2008): S78—S84. http://dx.doi.org/10.1055/s-2008-1080911.

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18

Maglio, Paul P. "Editorial Column—Modeling Complex Service Systems." Service Science 3, no. 4 (December 2011): i—ii. http://dx.doi.org/10.1287/serv.3.4.i.

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19

Nakamori, Y., and Y. Sawaragi. "Complex systems analysis and environmental modeling." European Journal of Operational Research 122, no. 2 (April 2000): 178–89. http://dx.doi.org/10.1016/s0377-2217(99)00227-1.

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20

Sayama, Hiroki, Irene Pestov, Jeffrey Schmidt, Benjamin James Bush, Chun Wong, Junichi Yamanoi, and Thilo Gross. "Modeling complex systems with adaptive networks." Computers & Mathematics with Applications 65, no. 10 (May 2013): 1645–64. http://dx.doi.org/10.1016/j.camwa.2012.12.005.

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21

Kreuzer, Edwin J. "Mathematical modeling of complex mechanical systems." Mathematical Modelling 8 (1987): 37–42. http://dx.doi.org/10.1016/0270-0255(87)90537-9.

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22

Wu, Jianguo, and Danielle Marceau. "Modeling complex ecological systems: an introduction." Ecological Modelling 153, no. 1-2 (July 2002): 1–6. http://dx.doi.org/10.1016/s0304-3800(01)00498-7.

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23

Truhlar, Donald G. "Molecular Modeling of Complex Chemical Systems." Journal of the American Chemical Society 130, no. 50 (December 17, 2008): 16824–27. http://dx.doi.org/10.1021/ja808927h.

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24

Liang Wang and R. Langari. "Complex systems modeling via fuzzy logic." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 26, no. 1 (1996): 100–106. http://dx.doi.org/10.1109/3477.484441.

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25

Korneev, Andrey Mastislavovich, Faisal Abdo Ali Al-Saeedi, Ghassan Mohsen Al-Sabry, Tatiana Andreevna Smetannikova, and Abdullh Mohammed Mohammed Nagi. "DISCRETE MODELING OF COMPLEX MANUFACTURING SYSTEMS." Theoretical & Applied Science 9, no. 01 (January 30, 2014): 32–35. http://dx.doi.org/10.15863/tas.2014.01.9.5.

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26

Kaplan, Bruce, Mike Mecherikoff, and Harold Blackman. "Solution Bias in Complex Systems Modeling." Proceedings of the Human Factors Society Annual Meeting 32, no. 13 (October 1988): 790–93. http://dx.doi.org/10.1518/107118188786762225.

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Анотація:

Each discipline tends to use analytic tools that lead them to solutions within their own discipline, and steer them away from others. Within a discipline, we tend to pose solutions that align with our areas of interest or expertise. Clients can be guided into work which may not be the best solution to their particular set of problems or needs.

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27

Balcerak, Ernie. "Modeling complex systems in the geosciences." Eos, Transactions American Geophysical Union 94, no. 10 (March 5, 2013): 104. http://dx.doi.org/10.1002/2013eo100013.

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28

Panayotova, Galina S., and Dimitar A. Dimitrov. "Modeling from Time Series of Complex Brain Signals." International Journal of Signal Processing Systems 9, no. 1 (March 2021): 1–6. http://dx.doi.org/10.18178/ijsps.9.1.1-6.

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Анотація:

Signals obtained from most of real-world systems, especially from living organisms, are irregular, often chaotic, non-stationary, and noise-corrupted. Since modern measuring devices usually realize digital processing of information, recordings of the signals take the form of a discrete sequence of samples (a time series). In the paper given a brief overview of the possibilities of such experimental data processing based on reconstruction and usage of a predictive empirical model of a time series. Brain signals can be recorded by brainwave controlled applications, such as EMotiv Epoc +14. The paper investigates the models of the observed brain signals using time series, analyzes their applicability and develops new statistical models for their study.

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29

Haimes, Yacov Y. "Modeling complex systems of systems with Phantom System Models." Systems Engineering 15, no. 3 (May 16, 2012): 333–46. http://dx.doi.org/10.1002/sys.21205.

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30

Metta, Giorgio, and Giulio Sandini. "Embodiment and complex systems." Behavioral and Brain Sciences 24, no. 6 (December 2001): 1068–69. http://dx.doi.org/10.1017/s0140525x01410120.

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Анотація:

In agreement with the target article, we would like to point out a few aspects related to embodiment which further support the position of biorobotics. We argue that, especially when complex systems are considered, modeling through a physical implementation can provide hints to comprehend the whole picture behind the specific set of experimental data.

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31

Garkina, Irina, Alexander Danilov, and Yuri Skachkov. "Modeling of Building Materials as Complex Systems." Key Engineering Materials 730 (February 2017): 412–17. http://dx.doi.org/10.4028/www.scientific.net/kem.730.412.

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Анотація:

We considered the problems of mathematical modeling of composite materials in the example of the development of materials for the protection against ionizing radiation. Construction materials are provided as a complex system with the appropriate attributes. The structure and physico-mechanical properties of the material were determined by the results of the modeling of kinetic processes. Process of forming properties is described by the differential equation in deviations from the equilibrium state (as for dispersion system). It is taken into account the elastic and damping properties of the material. To predict the behavior of the building material and the formation of his private mathematical models are used a representation of the processes as of time series. It is given the algorithm for studies (with considering prehistory) of formation of the basic physical and mechanical properties of epoxy composites for radiation protection. We present an example of the identification of building materials with special properties. Approaches used effectively in the development of materials with special properties.

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32

Bila, Jiri, Ali H. Reshak, and Jan Chysky. "Modeling Complex Systems by Structural Invariants Approach." Complexity 2021 (September 4, 2021): 1–17. http://dx.doi.org/10.1155/2021/6650619.

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Анотація:

When modeling complex systems, we usually encounter the following difficulties: partiality, large amount of data, and uncertainty of conclusions. It can be said that none of the known approaches solves these difficulties perfectly, especially in cases where we expect emergences in the complex system. The most common is the physical approach, sometimes reinforced by statistical procedures. The physical approach to modeling leads to a complicated description of phenomena associated with a relatively simple geometry. If we assume emergences in the complex system, the physical approach is not appropriate at all. In this article, we apply the approach of structural invariants, which has the opposite properties: a simple description of phenomena associated with a more complicated geometry (in our case pregeometry). It does not require as much data and the calculations are simple. The price paid for the apparent simplicity is a qualitative interpretation of the results, which carries a special type of uncertainty. Attention is mainly focused (in this article) on the invariant matroid and bases of matroid (M, BM) in combination with the Ramsey graph theory. In addition, this article introduces a calculus that describes the emergent phenomenon using two quantities—the power of the emergent phenomenon and the complexity of the structure that is associated with this phenomenon. The developed method is used in the paper for modeling and detecting emergent situations in cases of water floods, traffic jams, and phase transition in chemistry.

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33

Chen, Lei, Xinghuo Yu, and Changyin Sun. "Characteristic Modeling Approach for Complex Network Systems." IEEE Transactions on Systems, Man, and Cybernetics: Systems 48, no. 8 (August 2018): 1383–88. http://dx.doi.org/10.1109/tsmc.2017.2737438.

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34

Toroptsev, E. L., A. S. Marahovskiy, and A. V. Babkin. "Complex Modeling of the Economic Systems Stability." IOP Conference Series: Earth and Environmental Science 272 (June 21, 2019): 032175. http://dx.doi.org/10.1088/1755-1315/272/3/032175.

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35

Zhang, Jie, Souma Chowdhury, Junqiang Zhang, Achille Messac, and Luciano Castillo. "Adaptive Hybrid Surrogate Modeling for Complex Systems." AIAA Journal 51, no. 3 (March 2013): 643–56. http://dx.doi.org/10.2514/1.j052008.

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36

Mosekilde, Erik, Olga V. Sosnovtseva, and Niels-Henrik Holstein-Rathlou. "Mechanism-Based Modeling of Complex Biomedical Systems." Basic Clinical Pharmacology Toxicology 96, no. 3 (March 2005): 212–24. http://dx.doi.org/10.1111/j.1742-7843.2005.pto960311.x.

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37

Stylios, C. D., and P. P. Groumpos. "Modeling Complex Systems Using Fuzzy Cognitive Maps." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 34, no. 1 (January 2004): 155–62. http://dx.doi.org/10.1109/tsmca.2003.818878.

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38

Zamula, Alina, and Sergii Kavun. "Complex systems modeling with intelligent control elements." International Journal of Modeling, Simulation, and Scientific Computing 08, no. 01 (January 10, 2017): 1750009. http://dx.doi.org/10.1142/s179396231750009x.

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Анотація:

The approach to managing complex systems through the usage of fuzzy technology in combination with the system-dynamic modeling is improved. The methods of system dynamics and artificial intelligence represented the research subject. Object of study includes process operation of complex systems. For the experiment selected banking system (BS) and commercial bank (CB) as its subsystem. The mathematical models of the BS and CBs are developed; elements of intelligent control are formalized. The knowledge base in the form of production rules is designed in the paper. Functions of fuzzy variables and their parameters are selected for building fuzzy models using Mamdani and Sugeno algorithms. The control impact and the functioning of intellectual decision support system for the prediction task are studied. The efficiency of scientific research on the example of the Ukrainian BS is evaluated.

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39

Surkova, Ekaterina, Anna Klonitskaya, and Elena Ermolaeva. "Modeling business processes of complex organizational systems." E3S Web of Conferences 164 (2020): 10040. http://dx.doi.org/10.1051/e3sconf/202016410040.

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Анотація:

The complex systems of the construction and industrial complex in the study of their properties and the general laws of functioning by methods of mathematical modeling require a systematic approach. Modeling is a complex multi-stage process of researching systems aimed at identifying the properties and patterns inherent in the studied systems in order to improve these systems. This article discusses the mathematical model of a complex socio-economic system, taking into account the quality indicators presented to the processes of this system. The analysis and design of the innovation system in the framework of technical regulation of activities. The result is a fundamentally new model of technical regulation taking into account the time factor in axonometric form.

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40

Hu, Guoqiang, Wenwu Yu, Guanghui Wen, Housheng Su, and Ying Tan. "Modeling and Control of Complex Networked Systems." Mathematical Problems in Engineering 2014 (2014): 1–2. http://dx.doi.org/10.1155/2014/831582.

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41

Li, Chuandong, Xiaodi Li, Shukai Duan, and Yanzhi Zhang. "Modeling, Analysis, and Applications of Complex Systems." Abstract and Applied Analysis 2013 (2013): 1. http://dx.doi.org/10.1155/2013/798173.

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42

Bottegal, Giulio, and Giorgio Picci. "Modeling Complex Systems by Generalized Factor Analysis." IEEE Transactions on Automatic Control 60, no. 3 (March 2015): 759–74. http://dx.doi.org/10.1109/tac.2014.2357913.

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43

BELLOMO, N., and F. BREZZI. "COMPLEX SYSTEMS: NEW CHALLENGES WITH MODELING HEADACHES." Mathematical Models and Methods in Applied Sciences 24, no. 02 (December 12, 2013): 213–19. http://dx.doi.org/10.1142/s0218202513020016.

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Анотація:

This brief note is an introduction to the papers published in this special issue devoted to complex systems in life sciences. Out of this presentation some perspective ideas on conceivable future research objectives are extracted and brought to the reader's attention. The final (ambitious) aim is to develop a mathematical theory for complex living systems.

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44

Todd, Eric M., and Steven C. Zimmerman. "Modeling the Equilibria of Complex Supramolecular Systems." Journal of Chemical Education 86, no. 5 (May 2009): 638. http://dx.doi.org/10.1021/ed086p638.

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45

Ryoke, Mina, and Yoshiteru Nakamori. "Agent-based approach to complex systems modeling." European Journal of Operational Research 166, no. 3 (November 2005): 717–25. http://dx.doi.org/10.1016/j.ejor.2004.03.041.

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46

Sivakumar, Bellie, and Ronny Berndtsson. "Modeling and prediction of complex environmental systems." Stochastic Environmental Research and Risk Assessment 23, no. 7 (September 23, 2008): 861–62. http://dx.doi.org/10.1007/s00477-008-0280-0.

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47

Li, Shu-Guang, Hua-Sheng Liao, and Chuen-Fa Ni. "Stochastic modeling of complex nonstationary groundwater systems." Advances in Water Resources 27, no. 11 (January 2004): 1087–104. http://dx.doi.org/10.1016/j.advwatres.2004.08.002.

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48

Luo, Guiming, Xiaoyu Song, Xiaojing Yang, Krishnaiyan Thulasiraman, Jean-François Monin, and Guowu Yang. "Modeling, Optimization, and Verification for Complex Systems." Mathematical Problems in Engineering 2016 (2016): 1–3. http://dx.doi.org/10.1155/2016/2458369.

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49

Hanczewski, Sławomir, Maciej Stasiak, and Michał Weissenberg. "Modeling of Complex Non-Full-Availability Systems." Journal of Telecommunications and Information Technology 2 (June 30, 2020): 70–77. http://dx.doi.org/10.26636/jtit.2020.143320.

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50

Bacha, Seddik, Hong Li, and Davis Montenegro-Martinez. "Complex Power Electronics Systems Modeling and Analysis." IEEE Transactions on Industrial Electronics 66, no. 8 (August 2019): 6412–15. http://dx.doi.org/10.1109/tie.2019.2901189.

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