Flood hydrograph simulation is affected by uncertainty in Rainfall – Runoff )RR( parameters. Uncertainty of RR parameters in Gharasoo catchment, part of the great Karkheh river basin, is evaluated by Monte–Carlo (MC) approach. A conceptual-distributed model, called ModClark, was used for basin simulation, in which the basin’s hydrograph was determined using the superposition of runoff generated...

Flood hydrograph simulation is affected by uncertainty in Rainfall – Runoff )RR( parameters. Uncertainty of RR parameters in Gharasoo catchment, part of the great Karkheh river basin, is evaluated by Monte–Carlo (MC) approach. A conceptual-distributed model, called ModClark, was used for basin simulation, in which the basin’s hydrograph was determined using the superposition of runoff generated...

We report on the RTGrid project, which investigates approaches for using high-performance computing infrastructures, such as the grid, in order to reduce the turnaround time of Monte Carlo (MC) simulation-based radiotherapy treatment planning. The main aim of this project is to render accurate dose calculations using MC simulations clinically feasible. To this end, we have successfully implemen...

background: the monte carlo method is the most accurate method for simulation of radiation therapy equipment. the linear accelerators are currently the most widely used machines in radiation therapy centers. methods: in this work, a monte carlo modelling of the siemens oncor linear accelerator in 6 mv and 18 mv beams was performed. the results of simulation were validated by measurements in wat...

Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. In the game of Lines of Action (LOA), which has been dominated in the past by αβ, MCTS is making an inroad. In this paper we investigate how to use a positional evaluation function in a Monte-Carlo simulation-based LOA program (MC-LOA). Four different simulation strategies are designed, called Evaluati...

Generalized Monte Carlo titration (GMCT) is a versatile suite of computer programs for the efficient simulation of complex macromolecular receptor systems as for example proteins. The computational model of the system is based on a microstate description of the receptor and an average description of its surroundings in terms of chemical potentials. The receptor can be modeled in great detail in...

In this work, we present a new three-dimensional Monte Carlo (MC) method which naturally recovers the realspace carrier-impurity Coulomb interaction by mesh-based resolution of Poisson’s equation. This method necessitates no additional modifications to the conventional MC simulator, thus simplifying the implementation process. The new method has been validated through the reproduction of the do...

Monte Carlo (MC) sampling methods are widely applied in Bayesian inference, system simulation and optimization problems. The Markov Chain Monte Carlo (MCMC) algorithms are a well-known class of MC methods which generate a Markov chain with the desired invariant distribution. In this document, we focus on the Metropolis-Hastings (MH) sampler, which can be considered as the atom of the MCMC techn...

We calculate analytically the dynamic critical exponent z(MC), measured in Monte Carlo simulations for a vortex loop model of the superconducting transition, and account for the simulation results. In the weak screening limit, where magnetic fluctuations are neglected, the dynamic exponent is found to be z(MC) = 3/2. In the perfect screening limit, z(MC) = 5/2. We relate z(MC) to the actual val...