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  1. 1
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
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  2. 2
    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction

    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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  3. 3
    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
    “…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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  4. 4
    Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction

    Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This is due to the fixed and limited combination offered for evaluation as well as the lack of higher-order interaction of combination. In response to this issue, this paper proposed an angle modulated Bat algorithm to be integrated with the T-method in optimizing the prediction model. …”
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  5. 5
    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 reweighted fast, consistent and high breakdown (RFCH) estimator is a multivariate procedure used to estimate the robust location and scatter matrix. …”
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  6. 6
    Solving large-scale problems using multi-swarm particle swarm approach

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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  7. 7
    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
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  8. 8
    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri

    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

    Published 2022
    “…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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  9. 9
    A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

    A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant by Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.

    Published 2023
    “…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
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  10. 10
    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search

    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

    Published 2014
    “…These problems resulted in estimation errors and high computational cost. Hybrid genetic algorithm (GA) and Nelder-Mead local search mode 1 has been used to minimize demand estimation errors. …”
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  11. 11
    Robust Estimation Methods And Outlier Detection In Mediation Models

    Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

    Published 2010
    “…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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  12. 12
    Model selection approaches of water quality index data

    Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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  13. 13
    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION

    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

    Published 2015
    “…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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  14. 14
    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus

    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

    Published 2016
    “…The significant variables determined by maximum likelihood method were then estimated using the BLR method. …”
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  15. 15
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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  16. 16
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
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  17. 17
    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali

    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali by Jarinah , Mohd Ali

    Published 2017
    “…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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  18. 18
    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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  19. 19
    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

    Published 2025
    “…Additionally, parametric and sensitivity analyses were used to assess the performance of the GPR and LR algorithms. …”
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  20. 20
    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)

    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Hence, the integration of EM algorithm estimation is applicable in improving the performance of automated model selection procedures for multiple equations models…”
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    Monograph
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