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  1. 1
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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  2. 2
    A Computationally Efficient Least Square Channel Estimation Method for MIMO-OFDM Systems

    A Computationally Efficient Least Square Channel Estimation Method for MIMO-OFDM Systems by Ahmad, Hasan, Motakabber, S. M. A., Anwar, Farhat, Habaebi, Mohamed Hadi, Ibrahimy, Muhammad Ibn

    Published 2021
    “…Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. …”
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  3. 3
    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model

    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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  4. 4
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. …”
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  5. 5
    Model selection approaches of water quality index data

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

    Published 2016
    “…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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  6. 6
    Orthogonal least square algorithm and its application for modelling suspension system

    Orthogonal least square algorithm and its application for modelling suspension system by Ahmad, Robiah, Jamaluddin, Hishamuddin

    Published 2001
    “…One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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  7. 7
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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  8. 8
    State estimation of the power system using robust estimator

    State estimation of the power system using robust estimator by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F.

    Published 2016
    “…In this study, a new robust algorithm based on the quasi weighted least squares (QWLS) estimator is presented. …”
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    Conference or Workshop Item
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  9. 9
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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  10. 10
    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm by Rashid, Roslina, Jamaluddin, Hishamuddin, Saidina Amin, Nor Aishah

    Published 2005
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  11. 11
    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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  12. 12
    Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms

    Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms by Bundak, Caceja Elyca

    Published 2021
    “…Another problem in MF IPS is there are few studies focused on using the Euclidean distance and the area between the reference points to improve the accuracy in the position estimation. Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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  13. 13
    Detection of multiple outliners in linear regression using nonparametric methods

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

    Published 2004
    “…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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  14. 14
    Mathematical modelling for estimating number of dengue cases in terengganu using cubic B-Spline method and discrete least square method / Nur Athirah Mazlan

    Mathematical modelling for estimating number of dengue cases in terengganu using cubic B-Spline method and discrete least square method / Nur Athirah Mazlan by Mazlan, Nur Athirah

    Published 2017
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  15. 15
    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method

    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method by Kaw, Wei Ching, Kek, Sie Long, Sim, Sy Yi

    Published 2017
    “…Least squares method, which is a statistical method with minimum sum squares of errors (SSE), is used for curve fitting and parameter estimation. …”
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  16. 16
    Reduced-rank technique for joint channel estimation in TD-SCDMA systems.

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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  17. 17
    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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  18. 18
    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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  19. 19
    Estimation of foreign workers in Malaysia by using Euler’s method and least square method / Nur Fatin Adibah Mohd Zin

    Estimation of foreign workers in Malaysia by using Euler’s method and least square method / Nur Fatin Adibah Mohd Zin by Mohd Zin, Nur Fatin Adibah

    Published 2021
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  20. 20
    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
    “…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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