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  1. 1
    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation

    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation by Umar, Roslan, -, Othman, -, A.P., -, Gopir

    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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  2. 2
    Characterization of dumping soil and settlement prediction using Monte Carlo approach

    Characterization of dumping soil and settlement prediction using Monte Carlo approach by Mohd Pauzi, Nur Irfah

    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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  3. 3
    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation

    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation by A. P. Othman, R. Umar, G. Gopir

    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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  4. 4
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  5. 5
    Simulation of single electron transistor (SET) circuits using Monte Carlo method

    Simulation of single electron transistor (SET) circuits using Monte Carlo method by Ahmad, Syabani

    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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  6. 6
    Monte Carlo simulation of micelle formation in mixed surfactants and palm-kernel oil esters-based nanoemulsion

    Monte Carlo simulation of micelle formation in mixed surfactants and palm-kernel oil esters-based nanoemulsion by Yahya, Ruzanna

    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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  7. 7
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  8. 8
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  9. 9
    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH

    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    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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  10. 10
    Cash-flow analysis of a wind turbine operator

    Cash-flow analysis of a wind turbine operator by Muhamad Razali N.M., Hashim A.H.

    Published 2023
    Conference Paper
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  11. 11
    Simple algorithm for estimating the effects of reinforcement loadings and arrangements on composite properties

    Simple algorithm for estimating the effects of reinforcement loadings and arrangements on composite properties by Wan Ibrahim, W. M. A, Yeoh, C. K., Teh, P.L., Khairel Rafezi, Ahmad, Ruhiyuddin , Mohd Zaki

    Published 2010
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  12. 12
    Adsorption of non-ionic surfactants on organoclays in drilling fluid investigated by molecular descriptors and Monte Carlo random walk simulations

    Adsorption of non-ionic surfactants on organoclays in drilling fluid investigated by molecular descriptors and Monte Carlo random walk simulations by Kania, Dina, Yunus, Robiah, Omar, Rozita, Abdul Rashid, Suraya, Mohamed Jan, Badrul, Aulia, Akmal

    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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  13. 13
    Optimal sizing of hybrid tidal, photovoltaic and battery sources of energy

    Optimal sizing of hybrid tidal, photovoltaic and battery sources of energy by Sadeghi, Omid Sarrafan

    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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  14. 14
    Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables

    Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables by ALAhmad A.K., Verayiah R., Ramasamy A., Marsadek M., Shareef H.

    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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  15. 15
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  16. 16
    Markov chain Monte Carlo convergence diagnostics for Gumbel model

    Markov chain Monte Carlo convergence diagnostics for Gumbel model by Mohd Amin, Nor Azrita, Adam, Mohd. Bakri

    Published 2016
    “…The MCMC technique, Metropolis-Hastings algorithm is used for posterior inferences of Gumbel distribution simulated data.…”
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  17. 17
    Slice sampler algorithm for generalized pareto distribution

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    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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  18. 18
    A modified weight optimisation for higher-order neural network in time series prediction

    A modified weight optimisation for higher-order neural network in time series prediction by Husaini, Noor Aida

    Published 2020
    “…The challenges in time series prediction are to provide a technique to better understand a dataset. In line with this, the Cuckoo Search (CS) learning algorithm, a kind of metaheuristics techniques employs high-level techniques for exploration and exploitation of the search space in which its step length is much longer in the long run. …”
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  19. 19
    Reconstruction algorithm of calibration map for RPT technique in quadrilateral bubble column reactor using MCNPX code

    Reconstruction algorithm of calibration map for RPT technique in quadrilateral bubble column reactor using MCNPX code by Mohd Yunos, Mohd Amirul Syafiq, Anak Usang, Mark Dennis, Ithnin, Hanafi, Hussain, Siti Aslina, Mohamed Yusoff, Hamdan, Sipaun, Susan

    Published 2018
    “…To validate the simulation precision, a spiral trajectory of radioactive particle inside the bubble column region consist of 84 grid point locations of the particle were applied. …”
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  20. 20
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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