Search Results - (( general selection methods algorithm ) OR ( carlo simulation approach algorithm ))*

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  1. 1

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…In general, both methods are performing well for analyzing extreme model but numerical results show that MTM method performs slightly better than MH method in terms of efficiency and convergency to the stationary distribution. …”
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    Thesis
  2. 2

    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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    Thesis
  3. 3

    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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    Article
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    Numerical Analysis of structural batteries response with the presence of uncertainty by Syahiir Kamil, Ahmad Kamal Ariffin, Abdul Hadi Azman, Mohamad Syazwan Zafwan Mohamad Suffian

    Published 2023
    “…Simulation results between the Interval Monte Carlo and Deterministic are compared to evaluate the significance of the uncertainty factor influences. …”
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    Article
  6. 6

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The reversible jump Markov Chain Monte Carlo (MCMC) algorithm is proposed to obtain the Bayesian estimator. …”
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    Article
  7. 7

    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
    “…The single radioactive particle emits γ-ray, and its movement in the column is tracked with the aid of arrays radiation detectors. In this study, Monte Carlo approach was programmed to reconstruct the particle tracer position so-called calibration map. …”
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    Article
  8. 8

    Numerical Analysis of Structural Batteries Response with the Presence of Uncertainty by Syahiir, Kamil, Mohamad Syazwan Zafwan, Mohamad Suffian, Ahmad Kamal Ariffin, Mohd Ihsan, Abdul Hadi, Azman

    Published 2023
    “…Simulation results between the Interval Monte Carlo and Deterministic are compared to evaluate the significance of the uncertainty factor influences. …”
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    Article
  9. 9

    Active control of high frequency vibration in uncertain structures by Abdul Muthalif, Asan Gani, Langley, Robin S

    Published 2006
    “…The aim of this paper is to numerically investigate the robustness of LQR and LQG algorithms by designing the controller for a nominal system, and then assessing (via Monte Carlo simulation) the effects of uncertainties in the system. …”
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    Proceeding Paper
  10. 10

    Evaluation of a spacecraft attitude and rate estimation algorithm by Abdullah, Mohammad Nizam Filipski, Varatharajoo, Renuganth

    Published 2010
    “…The assessment of the algorithm performance is realized through a Monte Carlo simulation using a low‐Earth orbit, nadir‐pointing satellite. …”
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    Article
  11. 11

    Comparing three methods of handling multicollinearity using simulation approach by Adnan, Norliza

    Published 2006
    “…For comparison purposes, mean square errors (MSE) were calculated. A Monte Carlo simulation study was used to evaluate the effectiveness of these three procedure. …”
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    Thesis
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    Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach by Rose, Farid Zamani Che

    Published 2023
    “…Based on the simulation results, the sequential selection algorithm outperformed the non-sequential selection approach in the automatic GETS model selection procedure. …”
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    Thesis
  14. 14

    Accurate range free localization in multi-hop wireless sensor networks by Abdulwahhab, Abdullah Raed

    Published 2019
    “…The performance is evaluated in terms of RMSE in terms of three algorithms WLS, CRLR, and GMSDP based on using the Monte Carlo simulation with account the number of anchors that varying from anchor=4 to anchor =20. …”
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    Thesis
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    Enhanced path planning for industrial robot: integrating modified artificial potential field and A* algorithm / Fan Rui ... [et al.] by -, Fan Rui, Ayub, Muhammad Azmi, Ab Patar, Mohd Nor Azmi, Che Abdullah, Sukarnur, Ahmat Ruslan, Fazlina

    Published 2024
    “…Kinematic and workspace analyses of the robot utilize the Denavit-Hartenberg and Monte Carlo methods. The study analyses the principles and limitations of classical algorithms. …”
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    Article
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    Position estimation comparison of a 3-D linear lateration algorithm with a reference selection technique by Yaro, A.S., Sha�Ameri, A.Z., Kamel, N.

    Published 2018
    “…Monte Carlo simulation result comparison shows that the four-GRS linear lateration algorithm with the GREPS technique outperformed the SF-TLS and MF-LS with a reduction in horizontal coordinate PE error of about 50 and 30 respectively, and with a 90 reduction in the altitude error. …”
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    Article
  17. 17

    Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

    Published 2004
    “…This reseach also provides a comparison between these three procedure to detect multiple outliers. A Monte Carlo simulations study was used to evaluate the effectiveness of these three procedures. …”
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    Monograph
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    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

    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. …”
    Article
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    Ground receiving station reference pair selection technique for a minimum configuration 3D emitter position estimation multilateration system by Yaro, A.S., Sha’Ameri, A.Z., Kamel, N.

    Published 2017
    “…Multilateration estimates aircraft position using the Time Difference Of Arrival (TDOA) with a lateration algorithm. The Position Estimation (PE) accuracy of the lateration algorithm depends on several factors which are the TDOA estimation error, the lateration algorithm approach, the number of deployed GRSs and the selection of the GRS reference used for the PE process. …”
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    Article
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