Search Results - (( carlo simulation a algorithm ) OR ( wave optimization path algorithm ))*
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. …”
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Application of parallel ensemble Monte Carlo technique in charge dynamics simulation
Published 2008“…When implementing this type of simulation on a single processor PCs using the conventional ensemble or single particle Monte Carlo method, the computational time is very long even on the fast 2.0 MHz PCs. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2021“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Characterization of dumping soil and settlement prediction using Monte Carlo approach
Published 2013“…These five models are simulated using Monte Carlo approaches. Monte Carlo simulation is a method employed an algorithm that must be used with repeated random sampling of uncertainty for ca. 50-5000 number of iterations in order to obtain the parameters such as primary compression ratio (X), secondary compression ratio compressive stress X compressive stress(A) and ultimate settlement (Sult)of the soil at the dumping area. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Application of parallel ensemble Monte Carlo technique in charge dynamics simulation
Published 2008“…When implementing this type of simulation on a single processor PCs using the conventional ensemble or single particle Monte Carlo method, the computational time is very long even on the fast 2.0 MHz PCs. …”
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Simulation of single electron transistor (SET) circuits using Monte Carlo method
Published 2007“…SET theory of operation is now well established nevertheless the transistor is still under laboratory investigations in the fields of fabrication and applications in Large Scale Integration (LSI). Simulation of SET consumes a great deal of computer time, which arises a need to renovate fast and accurate simulation algorithms. …”
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Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Monte Carlo simulation of micelle formation in mixed surfactants and palm-kernel oil esters-based nanoemulsion
Published 2014“…The physical properties of the mixed surfactants and nanoemulsions formulation were studied using the Metropolis Monte Carlo (MMC) algorithm while grand canonical Monte Carlo (GCMC) simulation was applied to investigate the displacements of critical micelle concentration (CMC) for both systems. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…For the load modelling studies, the Monte Carlo simulation is performed in Gaussian PDF to develop a probability model of various types of loads. …”
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Adsorption of non-ionic surfactants on organoclays in drilling fluid investigated by molecular descriptors and Monte Carlo random walk simulations
Published 2021“…Here, the fundamental phenomena involved in non-ionic surfactant adsorption on organoclays and how it affects the rheology of synthetic-based drilling fluids were elucidated by the analysis of molecular descriptors and Monte Carlo simulations. Using the Random Forests machine learning algorithm software, the non-ionic surfactant adsorption on organoclays was found to be affected mainly by the hydrophobicity and molecular shape of hydrophobic chains of non-ionic surfactants. …”
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Optimal sizing of hybrid tidal, photovoltaic and battery sources of energy
Published 2015“…Moreover, the sizing problem is also investigated without considering the uncertainty with the average data of sun irradiation and water velocity. The results of simulation with average data reveals that the total cost is 21% less than the cost which uncertainty is taken into account in renewable sources with Monte Carlo method, however the reliability index for the simulation with the average data calculated with the Monte Carlo method, shows that the system reliability in this case is, 177% less than ideal reliability index. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems
Published 2022“…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables
Published 2025“…The Quasi-Monte Carlo simulation (QMCS) method is adopted to generate multiple scenarios for a combination of wind, PV, load and electricity price uncertainties. …”
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Markov chain Monte Carlo convergence diagnostics for Gumbel model
Published 2016“…The MCMC technique, Metropolis-Hastings algorithm is used for posterior inferences of Gumbel distribution simulated data.…”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. …”
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