Search Results - (( based optimization method algorithm ) OR ( carlo simulation method algorithm ))*
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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2
Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy
Published 2019“…Additionally, the efficiency of the planned algorithm in numerical simulation was compared to that of the "Monte Carlo simulation" (MCS).…”
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3
Optimization of RFID network planning using MDB-FA method
Published 2017“…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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4
A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin
Published 2018“…These line search methods are tested based on six standard optimization test problems. …”
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5
Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration
Published 2025“…Moreover, to account for uncertainties related to various input random variables such as wind speed, solar irradiation, load power, and energy prices, Monte Carlo Simulation (MCS) is employed to generate multiple scenarios. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…Besides, the Monte-Carlo simulations demonstrated that all the values lie within the 95% confidence level. …”
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8
Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra...
Published 2025“…To address uncertainties in wind speed, solar irradiation, load demands, and energy prices, Monte Carlo Simulation (MCS) is employed. Scenario reduction through the Backward Reduction Algorithm (BRA) manages computational complexity. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. The Monte Carlo simulation (MCS) method enables an accurate evaluation of reliability indices. …”
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10
Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the first step, the hybrid Autoregressive Moving Average – Monte Carlo method proposes to simulate the hourly wind speed as well as the hourly wind turbine generators. …”
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11
A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties
Published 2020“…Several other strategies pertaining to achieve desired CSD with minimum amount of fine crystals were deployed. The optimization algorithm was employed in order to determine the optimal set-point trajectory for closed-loop control. …”
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13
Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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14
Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology
Published 2025“…A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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16
Characterization of dumping soil and settlement prediction using Monte Carlo approach
Published 2013“…The expected outcome of the research is settlement prediction model of closed dumping area for post-development using Monte Carlo simulation. The predicted settlement by Monte Carlo simulation method could save time and cost. …”
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Optimal sizing of hybrid tidal, photovoltaic and battery sources of energy
Published 2015“…In addition the reliability factor that is proposed with the Monte Carlo method is regarded as the ideal reliability index. …”
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19
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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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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