Sequential simulation has emerged as a robust and fast method for generating stochastic realizations. The recent development of a sequential simulation method by drawing structures from training images allows generating a wide variety of geological styles in a controlled fashion. Various methods for conditioning realizations to secondary information from geophysical or remote sensing techniques...

This paper describes how to achieve a desired speedup by careful selection of appropriate algorithms for parallelization. Our target simulation is the Total Airport and Airspace Model (TAAM), a worldwide standard for aviation analysis. TAAM is designed as a sequential program, and we have increased its speed by incorporating multithreaded algorithms with minimal changes to the underlying simula...

We propose fully sequential indifference-zone selection procedures that are specifically for use within an optimizationvia-simulation algorithm when simulation is costly and partial or complete information on solutions previously visited is maintained. Sequential Selection with Memory guarantees to select the best or near-best alternative with a user-specified probability when some solutions ha...

Modelling, synthesis, and simulation issues of the supervisory systems in process control are investigated in the paper. Petri nets are used as a basic modelling framework for the supervisory part of the system. It is shown how the final verification effort can be minimised by applying formal synthesis methods. A straightforward approach to the industrial implementation of the developed solutio...

The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-based investigations are common approaches in simulation and optimization. Sequential parameter optimization has been developed, because there is a strong need for sound statistical analysis of simulation and optimizat...

The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-based investigations are common approaches in simulation and optimization. Sequential parameter optimization has been developed, because there is a strong need for sound statistical analysis of simulation and optimizat...

This paper describes how to achieve a desired speedup by careful selection of appropriate algorithms for parallelization. Our target simulation is the Total Airport and Airspace Model (TAAM), a worldwide standard for aviation analysis. TAAM is designed as a sequential program, and we have increased its speed by incorporating multithreaded algorithms with minimal changes to the underlying simula...

Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data and the result of deterministic inversion is smooth. Low frequency component is obtained fro...

Simulation is a widely used tool in evaluating and guiding high-level hardware design decisions. As a result, the accuracy of the simulation model is critical; a poor model can result in poor design choices. Since most simulation models are complex, some form of validation is needed to ensure this accuracy. The most common validation technique is that of checking the simulation model by hand. C...