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Статті в журналах з теми "Modeling Complex Systems"
Xepapadeas, Anastasios. "Modeling complex systems." Agricultural Economics 41 (November 2010): 181–91. http://dx.doi.org/10.1111/j.1574-0862.2010.00499.x.
Повний текст джерелаSchreckenberg, 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.
Повний текст джерелаCostanza, 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.
Повний текст джерелаKondratiev, 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.
Повний текст джерелаMirchandani, Chandru. "Resilience Modeling in Complex Systems." Procedia Computer Science 168 (2020): 232–40. http://dx.doi.org/10.1016/j.procs.2020.02.262.
Повний текст джерелаRachdi, 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.
Повний текст джерелаMakowski, 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.
Повний текст джерелаShlesinger, 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.
Повний текст джерелаFilev, 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.
Повний текст джерелаWeisbuch, Gérard. "Modeling complex systems: Do it!" Complexity 11, no. 3 (January 2006): 25–26. http://dx.doi.org/10.1002/cplx.20113.
Повний текст джерелаДисертації з теми "Modeling Complex Systems"
Müller, Thorsten G. "Modeling complex systems with differential equations." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10236319.
Повний текст джерелаAzevedo, Kyle Kellogg. "Modeling sustainability in complex urban transportation systems." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37289.
Повний текст джерелаGuan, Jinyan. "Bayesian generative modeling for complex dynamical systems." Thesis, The University of Arizona, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10109036.
Повний текст джерелаThis dissertation presents a Bayesian generative modeling approach for complex dynamical systems for emotion-interaction patterns within multivariate data collected in social psychology studies. While dynamical models have been used by social psychologists to study complex psychological and behavior patterns in recent years, most of these studies have been limited by using regression methods to fit the model parameters from noisy observations. These regression methods mostly rely on the estimates of the derivatives from the noisy observation, thus easily result in overfitting and fail to predict future outcomes. A Bayesian generative model solves the problem by integrating the prior knowledge of where the data comes from with the observed data through posterior distributions. It allows the development of theoretical ideas and mathematical models to be independent of the inference concerns. Besides, Bayesian generative statistical modeling allows evaluation of the model based on its predictive power instead of the model residual error reduction in regression methods to prevent overfitting in social psychology data analysis.
In the proposed Bayesian generative modeling approach, this dissertation uses the State Space Model (SSM) to model the dynamics of emotion interactions. Specifically, it tests the approach in a class of psychological models aimed at explaining the emotional dynamics of interacting couples in committed relationships. The latent states of the SSM are composed of continuous real numbers that represent the level of the true emotional states of both partners. One can obtain the latent states at all subsequent time points by evolving a differential equation (typically a coupled linear oscillator (CLO)) forward in time with some known initial state at the starting time. The multivariate observed states include self-reported emotional experiences and physiological measurements of both partners during the interactions. To test whether well-being factors, such as body weight, can help to predict emotion-interaction patterns, We construct functions that determine the prior distributions of the CLO parameters of individual couples based on existing emotion theories. Besides, we allow a single latent state to generate multivariate observations and learn the group-shared coefficients that specify the relationship between the latent states and the multivariate observations.
Furthermore, we model the nonlinearity of the emotional interaction by allowing smooth changes (drift) in the model parameters. By restricting the stochasticity to the parameter level, the proposed approach models the dynamics in longer periods of social interactions assuming that the interaction dynamics slowly and smoothly vary over time. The proposed approach achieves this by applying Gaussian Process (GP) priors with smooth covariance functions to the CLO parameters. Also, we propose to model the emotion regulation patterns as clusters of the dynamical parameters. To infer the parameters of the proposed Bayesian generative model from noisy experimental data, we develop a Gibbs sampler to learn the parameters of the patterns using a set of training couples.
To evaluate the fitted model, we develop a multi-level cross-validation procedure for learning the group-shared parameters and distributions from training data and testing the learned models on held-out testing data. During testing, we use the learned shared model parameters to fit the individual CLO parameters to the first 80% of the time points of the testing data by Monte Carlo sampling and then predict the states of the last 20% of the time points. By evaluating models with cross-validation, one can estimate whether complex models are overfitted to noisy observations and fail to generalize to unseen data. I test our approach on both synthetic data that was generated by the generative model and real data that was collected in multiple social psychology experiments. The proposed approach has the potential to model other complex behavior since the generative model is not restricted to the forms of the underlying dynamics.
Guan, Jinyan. "Bayesian Generative Modeling of Complex Dynamical Systems." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/612950.
Повний текст джерелаValenzuela, Vega Rene Cristian. "Compact reliability and maintenance modeling of complex repairable systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51850.
Повний текст джерелаLe, Xuan Tuan. "Understanding complex systems through computational modeling and simulation." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEP003.
Повний текст джерелаTraditional approaches are not sufficient, and sometimes impossible in dealing with complexity issues such as emergence, self-organization, evolution and adaptation of complex systems. As illustrated in this thesis by the practical work of the author in a real-life project, the spreading of infectious disease as well as interventions could be considered as difusion processes on complex networks of heterogeneous individuals in a society which is considered as a reactive system. Modeling of this system requires explicitly specifying of each individual’s behaviors and (re)actions, and transforming them into computational model which has to be flexible, reusable, and ease of coding. Statechart, typical for model-based programming, is a good solution that the thesis proposes. Bottom-up agent based simulation finds emergence episodes in what-if scenarios that change rules governing agent’s behaviors that requires agents to learn to adapt with these changes. Decision tree learning is proposed to bring more flexibility and legibility in modeling of agent’s autonomous decision making during simulation runtime. Our proposition for computational models such as agent based models are complementary to traditional ones, and in some case they are unique solutions due to legal, ethical issues
Ding, Limei. "On modeling and control of complex dynamic systems." Licentiate thesis, Luleå, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26097.
Повний текст джерелаGodkänd; 2000; 20070318 (ysko)
Clark, Kenneth A. "Modeling single-event transients in complex digital systems." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Jun%5FClark%5FKenneth%5Fphd.pdf.
Повний текст джерелаSommerer, Christa. "Modeling complex adaptive systems and complexity for interactive art." Thesis, University of South Wales, 2002. https://pure.southwales.ac.uk/en/studentthesis/modeling-complex-adaptive-systems-and-complexity-for-interactive-art(3d7143e3-eb05-49b9-8965-0ffa53767eb9).html.
Повний текст джерелаDing, Limei. "Modeling control and analysis of complex dynamic chemical systems /." Luleå, 2003. http://epubl.luth.se/1402-1544/2003/28.
Повний текст джерелаКниги з теми "Modeling Complex Systems"
Modeling complex systems. New York: Springer, 2004.
Знайти повний текст джерелаNebraska--Lincoln), Nebraska Symposium on Motivation (52nd 2007 University of. Modeling complex systems. Lincoln, [Neb.]: University of Nebraska Press, 2007.
Знайти повний текст джерелаModeling complex systems. 2nd ed. New York: Springer, 2010.
Знайти повний текст джерелаBoccara, Nino. Modeling Complex Systems. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6562-2.
Повний текст джерелаGrunn, Emmanuel, and Anh Tuan Pham. Modeling of Complex Systems. West Sussex, England: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118579978.
Повний текст джерелаRivail, Jean-Louis, Manuel Ruiz-Lopez, and Xavier Assfeld, eds. Quantum Modeling of Complex Molecular Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21626-3.
Повний текст джерелаHashimoto, Koichi, Yasuaki Oishi, and Yutaka Yamamoto, eds. Control and Modeling of Complex Systems. Boston, MA: Birkhäuser Boston, 2003. http://dx.doi.org/10.1007/978-1-4612-0023-9.
Повний текст джерелаSiegfried, Robert. Modeling and Simulation of Complex Systems. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-07529-3.
Повний текст джерелаHaimes, Yacov Y. Modeling and Managing Interdependent Complex Systems of Systems. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119173670.
Повний текст джерелаGrigoʹevich, Ivakhnenko Alekseĭ, ed. Inductive learning algorithms for complex systems modeling. Boca Raton: CRC Press, 1994.
Знайти повний текст джерелаЧастини книг з теми "Modeling Complex Systems"
Mobus, George E., and Michael C. Kalton. "Systems Modeling." In Understanding Complex Systems, 645–98. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1920-8_13.
Повний текст джерелаHester, Patrick T., and Kevin MacG Adams. "Complex Systems Modeling." In Systemic Decision Making, 101–25. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54672-8_5.
Повний текст джерелаJavarone, Marco Alberto. "Modeling Complex Systems." In SpringerBriefs in Complexity, 15–31. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70205-6_2.
Повний текст джерелаHartley, Dean S. "Modeling Research." In Understanding Complex Systems, 39–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51935-7_3.
Повний текст джерелаFrank, Till D. "Modeling Interventions." In Understanding Complex Systems, 217–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97178-6_8.
Повний текст джерелаLiu, Sifeng, and Yi Lin. "Grey Systems Modeling." In Understanding Complex Systems, 107–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16158-2_4.
Повний текст джерелаHaefner, James W. "Complex Adaptive Systems." In Modeling Biological Systems, 424–37. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_20.
Повний текст джерелаHelbing, Dirk. "Agent-Based Modeling." In Understanding Complex Systems, 25–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24004-1_2.
Повний текст джерелаHartley, Dean S. "Modeling Unconventional Conflict." In Understanding Complex Systems, 171–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51935-7_7.
Повний текст джерелаElmqvist, H., S. E. Mattsson, M. Otter, and K. J. Åström. "Modeling Complex Physical Systems." In Control of Complex Systems, 21–38. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0349-3_2.
Повний текст джерелаТези доповідей конференцій з теми "Modeling Complex Systems"
Amit, Daniel J. "Modeling active memory: Experiment, theory and simulation." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386815.
Повний текст джерелаCampa, A. "Traveling bubbles in a model of DNA." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386846.
Повний текст джерелаSigmund, Karl. "Complex adaptive systems and the evolution of reciprocation." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386816.
Повний текст джерелаSzabó, György. "On the role of external constraints in a spatially extended evolutionary prisoner’s dilemma game." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386817.
Повний текст джерелаTella, J. L. "A model for predation pressure in colonial birds." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386818.
Повний текст джерелаThurner, Stefan. "A dynamical thermostat approach to financial asset price dynamics." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386819.
Повний текст джерелаIto, H. M. "Introduction to mathematical modeling of earthquakes." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386820.
Повний текст джерелаMarchetti, R. "The fractal properties of internet." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386821.
Повний текст джерелаGabrielli, A. "Etching of random solids: Hardening dynamics and self-organized fractality." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386822.
Повний текст джерелаIvanov, Plamen Ch. "Generating power-law tails in probability distributions." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386823.
Повний текст джерелаЗвіти організацій з теми "Modeling Complex Systems"
Aceves, Alejandro, and Todd Kapitula. Modeling Complex Nonlinear Optical Systems. Fort Belvoir, VA: Defense Technical Information Center, July 2006. http://dx.doi.org/10.21236/ada459336.
Повний текст джерелаChassin, David P., Joel M. Malard, Christian Posse, Asim Gangopadhyaya, Ning Lu, Srinivas Katipamula, and J. V. Mallow. Modeling Power Systems as Complex Adaptive Systems. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/877087.
Повний текст джерелаWerner, Brad. Modeling Nearshore Processes as Complex Systems. Fort Belvoir, VA: Defense Technical Information Center, July 2003. http://dx.doi.org/10.21236/ada416942.
Повний текст джерелаCooper, Curtis S., Aaron L. Bramson, and Arlo L. Ames. Intrinsic Uncertainties in Modeling Complex Systems. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1156599.
Повний текст джерелаMitter, Sanjoy K. Environments for Modeling and Simulation of Complex Systems. Fort Belvoir, VA: Defense Technical Information Center, June 1998. http://dx.doi.org/10.21236/ada394745.
Повний текст джерелаBusch, Timothy E., and Dawn A. Trevisani. Modeling of Complex Adaptive Systems in Air Operations. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada457738.
Повний текст джерелаSoloviev, Volodymyr Mykolayovych, and Viktoriya Volodymyrivna Solovyova. Universal tools of modeling different nature complex systems. ФОП Однорог Т.В., 2018. http://dx.doi.org/10.31812/123456789/2865.
Повний текст джерелаBeck, Thomas, Nimal Wijesekera, David Rogers, and Roman Petrenko. Multiscale Modeling of Complex Systems Conformational Transitions in Proteins. Fort Belvoir, VA: Defense Technical Information Center, October 2006. http://dx.doi.org/10.21236/ada482296.
Повний текст джерелаSaptsin, Vladimir, and Володимир Миколайович Соловйов. Relativistic quantum econophysics – new paradigms in complex systems modelling. [б.в.], July 2009. http://dx.doi.org/10.31812/0564/1134.
Повний текст джерелаMayo, Jackson R., and Robert C. Armstrong. Notes on "Modeling, simulation and analysis of complex networked systems". Office of Scientific and Technical Information (OSTI), March 2009. http://dx.doi.org/10.2172/984134.
Повний текст джерела