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TVCG
2008
111views more  TVCG 2008»
13 years 9 months ago
Two-Way Coupled SPH and Particle Level Set Fluid Simulation
Grid-based methods have difficulty resolving features on or below the scale of the underlying grid. Although adaptive methods (e.g., RLE, octrees) can alleviate this to some degree...
Frank Losasso, Jerry O. Talton, Nipun Kwatra, Rona...
IPPS
2010
IEEE
13 years 7 months ago
Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs
The Coarse-Grained Monte Carlo (CGMC) method is a multi-scale stochastic mathematical and simulation framework for spatially distributed systems. CGMC simulations are important too...
Lifan Xu, Michela Taufer, Stuart Collins, Dionisio...
KESAMSTA
2007
Springer
14 years 3 months ago
Reinforcement Learning on a Futures Market Simulator
: In recent years, market forecasting by machine learning methods has been flourishing. Most existing works use a past market data set, because they assume that each trader’s in...
Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fuk...
PRIMA
2007
Springer
14 years 3 months ago
An Agent Modeling Method Based on Scenario Rehearsal for Multiagent Simulation
Multiagent Systems are potential computational systems for various practical applications, tools, and so on. Multiagent simulation is one of the remarkable application to evaluate ...
Shohei Yamane, Toru Ishida
GRID
2004
Springer
14 years 2 months ago
On The Feasibility of Running Entity-Level Simulations on Grid Platforms
Scientists have long relied on abstract models to study phenomena that are too complex for direct observation and experimentation. As new scientific modeling methodologies emerge...
Alan Su, Francine Berman, Henri Casanova