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  1. 1
    Comparing three methods of handling multicollinearity using simulation approach

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

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
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  2. 2
    Neighbour-based on-demand routing algorithms for mobile ad hoc networks

    Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

    Published 2017
    “…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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  3. 3
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…Simulation and empirical studies are conducted in validating the performance of the two algorithms. …”
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  4. 4
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  5. 5
    A Comparative Study On Some Methods For Handling Multicollinearity Problems

    A Comparative Study On Some Methods For Handling Multicollinearity Problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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  6. 6
    A comparative study on some methods for handling multicollinearity problems

    A comparative study on some methods for handling multicollinearity problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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  7. 7
    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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  8. 8
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Various experiments were carried out to assess and test components of IFS algorithm. The first test was designed to evaluate the formulated IFS Selection Criterion Strategy (MI estimator) by comparing it with six different MI estimator benchmarks. …”
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  9. 9
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…To evaluate the efficiency of the proposed method, comprehensive contaminated models are designed and simulated. …”
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  10. 10
    Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission

    Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission by Ahmad Suki, Che Mohamed Arif

    Published 2011
    “…It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). …”
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  11. 11
    Potential Evapotranspiration Estimation Methods for Water Balance Analysis Using SWAT: A Case Study of Kelantan River Basin, Kelantan

    Potential Evapotranspiration Estimation Methods for Water Balance Analysis Using SWAT: A Case Study of Kelantan River Basin, Kelantan by Husain M.K., Hayder G., Mohd Sidek L., Ahmed A.N., Kushiar K.F.

    Published 2023
    “…29.3% and ?28.5%. The P-M method tends to estimate lower PET than HG and P-T with yearly simulated was accounted for approximately 66%, 70%, and 71% respectively of annual precipitation. …”
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  12. 12
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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  13. 13
    Neural network based adaptive pid controller for shell-and-tube heat exchanger

    Neural network based adaptive pid controller for shell-and-tube heat exchanger by Othman, Mohamad Hakimi

    Published 2019
    “…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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  14. 14
    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article

    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article by Othman, Mohamad Hakimi

    Published 2019
    “…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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  15. 15
    Development of robust procedures for partial least square regression with application to near infrared spectral data

    Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

    Published 2021
    “…The nonlinear solutions coupled with some improved robust methods such as Diagnostic Robust Generalized Potential (DRGP) method and GM6-Estimator are also introduced. …”
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  16. 16
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The speed for the sensorless vector control and closed loop V/F controllers is evaluated through the model reference adaptive control estimator. …”
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  17. 17
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The proposed method inherits the robustness properties of the original RFCH estimators. …”
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  18. 18
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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  19. 19
    Railway wheelset parameter estimation using signals from lateral velocity sensor

    Railway wheelset parameter estimation using signals from lateral velocity sensor by Selamat, H., Alimin, A. J., Sam, Y.M.

    Published 2008
    “…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state. …”
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  20. 20
    Parameter estimation of a continuous-time plant – the least-absolute error with variable forgetting factor method

    Parameter estimation of a continuous-time plant – the least-absolute error with variable forgetting factor method by Selamat, Hazlina, Yusof, Rubiyah, Goodall, Roger M.

    Published 2005
    “…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state.…”
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