dc.contributor.authorQuax, Rick.
dc.contributor.authorBader, David A.
dc.contributor.authorSloot, Peter M. A.
dc.identifier.citationQuax, R., Bader, D. A., & Sloot, P. M. A. (2011). SEECN: Simulating Complex Systems Using Dynamic Complex Networks. International Journal for Multiscale Computational Engineering, 9(2), 201-214.en_US
dc.description.abstractMultiscale, multiphysics systems are too complex for traditional mathematical modeling and require numerical simulation, yet such systems arise everywhere from modeling the immune system and protein interaction to epidemic spread in a human population. Unfortunately, at present researchers create their own ad hoc programs for their particular study. To address this problem we present the simulator for efficient evolution on complex networks (SEECN), an expressive simulator of complex systems that optimizes for both single-core and parallel performance. In SEECN, a complex network represents the system where the nodes and edges have specified properties that dictate the dynamics of the network over time. Our application is a detailed model of HIV spread among men who have sex with men and serves to show the simulator's expressiveness and to evaluate its performance.en_US
dc.relation.ispartofseriesInternational Journal for Multiscale Computational Engineeringen_US
dc.rights© 2011 Begell House.en_US
dc.titleSEECN : simulating complex systems using dynamic complex networksen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Computer Engineeringen_US

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