The enormous computing demands of AI and high-performance computing (HPC) applications are putting intense pressure on every ...

Cellular dynamics are intrinsically noisy, so mechanistic models must incorporate stochasticity if they are to adequately model experimental observations. As well as intrinsic stochasticity in gene ...

This is a preview. Log in through your library . Abstract (1) Spatial processes in an acarine predator-prey system were simulated by a stochastic population model. (2) The model describes interactions ...

Erkyihun S.T., E Zagona, B. Rajagopalan, (2017). “Wavelet and Hidden Markov-Based Stochastic Simulation Methods Comparison on Colorado River Streamflow,” Journal of Hydrologic Engineering 2017, 22(9): ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

ABSTRACTInterval-based simulation (IBS) has been proposed to model input uncertainty in discrete-event simulation. The foundation of this new simulation paradigm is imprecise probability, which models ...

This paper documents the specification of a model that was constructed to assess debt sustainability in emerging market economies. Key features of the model include external and fiscal sectors, which ...

This course is compulsory on the MSc in Quantitative Methods for Risk Management. This course is available on the MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in ...

This course is available on the MSc in Applicable Mathematics, MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in Operations Research & Analytics, MSc in Quantitative ...