EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 10 / No 3 (2015) Math. Model. Nat. Phenom., 10 3 (2015) 71-90 References
Free Access
Issue
Math. Model. Nat. Phenom.
Volume 10, Number 3, 2015
Model Reduction
Page(s) 71 - 90
DOI https://doi.org/10.1051/mmnp/201510307
Published online 22 June 2015
  1. E. Blanchart, N. Marilleau, J.L. Chotte, A. Drogoul, E. Perrier, C. Cambier. Sworm: an agent-based model to simulate the effect of earthworms on soil structure. European Journal of Soil Science, 60 (1) (2009), 13–21. [CrossRef] [Google Scholar]
  2. J. Buhl, D.J.T. Sumpter, I.D. Couzin, J.J. Hale, E. Despland, E.R. Miller, S.J. Simpson. From disorder to order in marching locusts. Science, 312 (5778) (2006), 1402–1406. [CrossRef] [PubMed] [Google Scholar]
  3. F. Castiglione, F. Pappalardo, M. Bernaschi, S. Motta. Optimization of HAART with genetic algorithms and agent-based models of HIV infection. Bioinformatics, 23 (24) 2007, 3350–3355. [CrossRef] [PubMed] [Google Scholar]
  4. R.R. Coifman, S. Lafon, A. Lee, M. Maggioni, B. Nadler, F. Warner, S. Zucker. Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods. Proceedings of the National Academy of Sciences of the United States of America, 102 (21) (2005), 7432-7437. [CrossRef] [PubMed] [Google Scholar]
  5. R.R. Coifman, S. Lafon, A.B. Lee, M. Maggioni, B. Nadler, F. Warner, S.W. Zucker. Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proceedings of the National Academy of Sciences of the United States of America, 102 (21) (2005), 7426-7431. [CrossRef] [PubMed] [Google Scholar]
  6. A. Dhooge, W. Govaerts, Y.A. Kuznetsov. MATCONT: a MATLAB package for numerical bifurcation analysis of ODEs. ACM Trans. Math. Softw., 29 (2) (2003), 141–164. [Google Scholar]
  7. E.J. Doedel, R.C. Paffenroth, A.R. Champneys, T.F. Fairgrieve, Y.A. Kuznetsov, B.E. Oldeman, B. Sandstede, X. Wang. AUTO 2000: Continuation and bifurcation software for ordinary differential equaitons (with HomCont). Technical Report. California Institute of Technology, Pasadena, CA, 2001. [Google Scholar]
  8. D.T. Gillespie. Markov Process. Academic Press, San Diego, 1992. [Google Scholar]
  9. L. Hamill, N. Gilbert. Social circles: A simple structure for agent-based social network models. The Journal of Artificial Societies and Social Simulation, 12 (2) (2009), 3. [Google Scholar]
  10. F.L. Hellweger, V. Bucci. A bunch of tiny individuals-individual-based modeling for microbes. Ecological Modelling, 220(1) (2009), 8–22. [CrossRef] [Google Scholar]
  11. E. Ilie-Zudor, L. Monostori. Agent-based framework for pre-contractual evaluation of participants in project-delivery supply-chains. Assembly Automation, 29 (2) (2009), 137–153. [CrossRef] [Google Scholar]
  12. M.A. Janssen, L.N. Alessa, M. Barton, S. Bergin, A. Lee. Towards a community framework for agent-based modelling. The Journal of Artificial Societies and Social Simulation, 11 (2) (2008), 6. [Google Scholar]
  13. I.G. Kevrekidis, C.W. Gear, G. Hummer. Equation-free: The computer-aided analysis of complex multiscale systems. AIChE Journal, 50 (7) (2004), 1346–1355. [CrossRef] [Google Scholar]
  14. I.G. Kevrekidis, C.W. Gear, J.M. Hyman, P.G. Kevrekidis, O. Runborg, C. Theodoropoulos. Equation-free coarse-grained multiscale computation: enabling microscopic simulators to perform system-level tasks. Comm. Math. Sciences, 1 (4) (2003), 715–762. [CrossRef] [Google Scholar]
  15. I.G. Kevrekidis, G. Samaey. Equation-free multiscale computation: Algorithms and applications. Annual Review of Physical Chemistry, 60 (2009), 321–344. [Google Scholar]
  16. B. Nadler, S. Lafon, R.R. Coifman, I.G. Kevrekidis. Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical Systems. Applied and Computational Harmonic Analysis, 21 (2006), 113-127. [CrossRef] [MathSciNet] [Google Scholar]
  17. I. Nishizaki, H. Katagiri, T. Oyama. Simulation analysis using multi-agent systems for social norms. Computational Economics, 34 (1) (2009), 37–65. [CrossRef] [Google Scholar]
  18. A. Omurtag, L. Sirovich. Modeling a large population of traders: Mimesis and stability. Journal of Economic Behavior & Organization, 61 (4) (2006), 562–576. [CrossRef] [Google Scholar]
  19. A. Pan, S.Y.S. Leung, K.L. Moon, K.W. Yeung. Optimal reorder decision-making in the agent-based apparel supply chain. Expert Systems with Applications, 36 (4) (2009), 8571–8581. [CrossRef] [Google Scholar]
  20. R. Pinnau. Model Reduction via Proper Orthogonal Decomposition. In Model Order Reduction: Theory, Research Aspects and Applications. W. A. Schilders, H. van der Vorst, J. Rommes, Eds. vol. 13. Springer, Berlin Heidelberg, (2008), 95-109. [Google Scholar]
  21. H. Risken. The Fokker-Planck Equation. Methods of Solution and Applications. Second edition. Springer, Berlin, 1989. [Google Scholar]
  22. O. Runborg, C. Theodoropoulos, I.G. Kevrekidis. Effective bifurcation analysis: a time-stepper-based approach. Nonlinearity, 15 (2) (2002), 491–511. [CrossRef] [Google Scholar]
  23. E. Samanidou, E. Zschischang, D. Stauffer, T. Lux. Agent-based models of financial markets. Reports on Progress in Physics, 70 (3) (2007), 409–450. [CrossRef] [Google Scholar]
  24. T. Shimokawa, K. Suzuki, T. Misawa. An agent-based approach to financial stylized facts. Physica A, 379 (1) (2007), 207–225. [CrossRef] [Google Scholar]
  25. C.I. Siettos, C.W. Gear, I.G. Kevrekidis. An equation-free approach to agent-based computation: bifurcation analysis and control of stationary states. Europhys. Lett., 99 (4) (2012), 48007. [CrossRef] [Google Scholar]
  26. J.B. Tenenbaum, V. de Silva, and J.C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290 (5500) (2000), 2319. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  27. B.C. Thorne, A.M. Bailey, S.M. Peirce. Combining experiments with multi-cell agent-based modeling to study biological tissue patterning. Briefings in Bioinformatics, 8 (4) (2007), 245–257. [CrossRef] [PubMed] [Google Scholar]
  28. D. Tykhonov, C. Jonker, S. Meijer, T. Verwaart. Agent-based simulation of the trust and tracing game for supply chains and networks. The Journal of Artificial Societies and Social Simulation, 11 (3) (2008), 1. [Google Scholar]
  29. F.H. Westerhoff. The use of agent-based financial market models to test the effectiveness of regulatory policies. Jahrbucher Fur Nationalokonomie Und Statistik, 228 (2-3) (2008), 195–227. [Google Scholar]
  30. L. Zhang, Z.H. Wang, J.A. Sagotsky, T.S. Deisboeck. Multiscale agent-based cancer modeling. Journal of Mathematical Biology, 58 (4-5) (2009), 545–559. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.