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Random walk on a graph is a simple stochastic procedure.
A stochastic procedure which realistically models imperfection sensitive composite shells is investigated in this paper.
At first, a stochastic procedure is proposed to be applied into optimization problems.
SubSim is an adaptive stochastic procedure to efficiently compute small failure probabilities, which are expressed as a product of large conditional failures probabilities by introducing intermediate failure events.
We propose a Monte Carlo form-finding method that employs a stochastic procedure to determine equilibrium configurations of a tensegrity structure.
We develop a fully Bayesian stochastic procedure, called mixed shrinkage prior (MSP), which performs both basis selection and coefficient evaluation simultaneously.
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Comprehensive stochastic procedures that look at the atypical features of rural contexts and include estimation errors into the design phase are strongly required.
This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on artificial neural network (ANN), computer simulation and design of experiments using stochastic procedures.
Although significant advances in deterministic methods have been made, stochastic procedures, specifically genetic algorithms, provide an attractive technology for solving these optimisation problems.
Although significant advances in deterministic methods have been made, stochastic procedures, especially Genetic Algorithms (GA), provide an attractive technology for solving these optimisation problems.
This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on genetic algorithm (GA), computer simulation and design of experiments using stochastic procedures.
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