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  1. 1
    A multiobjective simulated Kalman filter optimization algorithm

    A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

    Published 2018
    “…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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  2. 2
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Based on the theoretical and fundamental research analysis the FUHS16 and UHDS16 algorithms using 16 × 16 block-based motion estimation formulations were developed. …”
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  3. 3
    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar

    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

    Published 2016
    “…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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    Thesis
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  4. 4
    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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    Thesis
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  5. 5
    Firefly Algorithm based LCL filtered grid-tied STATCOM design for reactive power compensation in SCIG based Micro-grid

    Firefly Algorithm based LCL filtered grid-tied STATCOM design for reactive power compensation in SCIG based Micro-grid by Saxena N.K., Gupta A.R., Mekhilef S., Gao W.D., Kumar A., Gupta V., Netto R.S., Kanungo A.

    Published 2023
    Article
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  6. 6
    Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors

    Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors by Riazoshams, Hossein

    Published 2010
    “…The ordinary Nonlinear Least Squares (NLLS) and the Maximum Likelihood Estimator (MLE) techniques are often used to estimate the parameters of nonlinear models. …”
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  7. 7
    Dual-Criteria Method For Determining Critical Plane Orientation For Multiaxial Fatigue Prediction Using A Genetic Algorithm

    Dual-Criteria Method For Determining Critical Plane Orientation For Multiaxial Fatigue Prediction Using A Genetic Algorithm by M., Kaamal, M. M., Rahman

    Published 2015
    “…It is required to maintain greater accuracy than the incremental angle methods used conventionally in critical plane searching algorithms. …”
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  8. 8
    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sim, Sy Yi, Chen, Chuei Yee

    Published 2021
    “…During the calculation procedure, the conjugate gradient algorithm is employed to solve the optimization problem, in turn, to update the adjusted parameters repeatedly for obtaining the optimal solution of the model used. …”
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  9. 9
    A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm

    A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

    Published 2015
    “…A new fatigue parameter is formulated based on stress-strain variables identified from various fatigue life models in order to deal with mean stress effects and non-proportional hardening. …”
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  10. 10
    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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  11. 11
    Extract Motion from Picture Sequence

    Extract Motion from Picture Sequence by MOHD SHAFIQ AHMAD DAHALAN, MOHD SHAFIQ

    Published 2008
    “…The algorithm is used as reference to create a coding input for the MATLAB, which is the software used in this project. …”
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    Final Year Project
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  12. 12
    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sim, Sy Yi, Yee Chen, Yee Chen

    Published 2021
    “…During the calculation procedure, the conjugate gradient algorithm is employed to solve the optimization problem, in turn, to update the adjusted parameters repeatedly for obtaining the optimal solution of the model used. …”
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  13. 13
    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sy, Sy Yi, Chuei, Yee Chen

    Published 2021
    “…During the calculation procedure, the conjugate gradient algorithm is employed to solve the optimization problem, in turn, to update the adjusted parameters repeatedly for obtaining the optimal solution of the model used. …”
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  14. 14
    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…As a result, 60% training with five hidden nodes demonstrated the best performance with R- value of 0.827 and MSE value of 52.283. The ANN-based models could serve as reliable and useful tools in estimating the WQI of the river.…”
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    Monograph
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  15. 15
    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
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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    Student Project
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  16. 16
    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
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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  17. 17
    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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  18. 18
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. …”
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  19. 19
    Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms

    Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

    Published 2023
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  20. 20
    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels

    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels by Uwaechia, Anthony Ngozichukwuka, Mahyuddin, Nor Muzlifah, Ain, Mohd Fadzil, Abdul Latiff, Nurul Muazzah, Za'bah, Nor Farahidah

    Published 2019
    “…Furthermore, we leverage the sparse nature of the massive MIMO-OFDM system to formulate the quantized AoDs estimation into a block-sparse signal recovery problem, where the measurement matrix is designed based on the estimated virtual AoD. …”
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