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TVCG
2008
111views more  TVCG 2008»
15 years 12 days 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...
143
Voted
IPPS
2010
IEEE
14 years 10 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...
81
Voted
KESAMSTA
2007
Springer
15 years 6 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...
117
Voted
PRIMA
2007
Springer
15 years 6 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
15 years 6 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