Computational analysis and modelling of wave propagation and interaction with objects are essential to help understand the fundamental problems of wave travelling. Though various methods have been proposed to model the wave propagation procedures, Monte Carlo simulation plays important role as an effective method to trace individual phone history, based on the statistics of large photon populat...

Genetic algorithms methods utilize the same optimization procedures as natural genetic evolution, in which a population is gradually improved by selection. We have developed a genetic algorithm search procedure suitable for use in protein folding simulations. A population of conformations of the polypeptide chain is maintained, and conformations are changed by mutation, in the form of conventio...

We present a simulation method which is based on discretization of the state space of the target distribution (or some of its components) followed by proper weighting of the simulated output. The method can be used in order to simplify certain Monte Carlo and Markov chain Monte Carlo algorithms. Its main advantage is that the autocorrelations of the weighted output almost vanish and therefore s...

We review uses of Tsallis statistical mechanics in the protein folding problem. Monte Carlo simulated annealing algorithm and generalized-ensemble algorithm with both Monte Carlo and stochastic dynamics algorithms are discussed. Simulations by these algorithms are performed for a penta peptide, Met-enkephalin. In particular, for generalized-ensemble algorithms, it is shown that from only one si...

A theoretical analysis of the Monte Carlo method for steady-state semiconductor device simulation, also known as the single-particle Monte Carlo method, is presented. At the outset of the formal treatment is the stationary Boltzmann equation supplemented by boundary conditions, which is transformed into an integral equation. The conjugate equation has been formulated in order to develop forward...

In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techniques. The framework naturally encompasses restless bandits, contextual bandits, and other bandit variants under a single inferential model. Despite the model’s generality, we propose efficient Monte Carlo algorithms t...

A deterministic simulation model for the calculation of sojourn time statistics is proposed. The model is designed for urban cells taking into account city movement in street pattern, traffic lights and crossings. Sojourn time and remaining sojourn time are assumed to be random variables that follow a gamma distribution. The parameters of gamma are found for several possible parameter values us...