Search Results - (( re estimation ((method algorithm) OR (means algorithm)) ) OR ( a simulation model algorithm ))*

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  1. 1
    Robust estimation methods for fixed effect panel data model having block-concentrated outliers

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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  2. 2
    Slice sampler algorithm for generalized pareto distribution

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…Finally, the slice sampler algorithm was employed to estimate the re- turn and risk values of investment in Malaysian gold market.…”
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  3. 3
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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  4. 4
    Automated Scaling Region of Interest with Iterative Edge Preserving in Forward-Backward Time-Stepping

    Automated Scaling Region of Interest with Iterative Edge Preserving in Forward-Backward Time-Stepping by Juliana, Binti Nawawi

    Published 2019
    “…Average RE is 61.94% for a circular shape in breast model, meanwhile attains RE of 4.17% for a U-shape object. …”
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  5. 5
    End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels

    End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

    Published 2021
    “…The Normalized Mean Square Error (NMSE) and the BER perfor�mances for different DVB-S2X system MODCODs are investigated and the results for these algorithms are compared with the conventional Minimum Mean Square Er�ror (MMSE) and Least Square (LS) channel estimation techniques. …”
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  6. 6
    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)

    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO) by Jasni, Mohamad Zain, Azrag, Mohammed Adam Kunna, Saiful Farik, Mat Yatin, Aldehim, Ghadah, Zuhaira, Muhammad Zain, Shaiba, Hadil, Alturki, Nazik, Sapiah, Sakri, Azlinah, Mohamed, Jaber, Aqeel S.

    Published 2024
    “…In this study, experimental data was used to estimate seven kinetic parameters. However, the numerical results of The Relative Error (RE) and the Mean Error (ME) reveal that the observed and anticipated data are in line with the results. …”
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  7. 7
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…To remedy this problem, Kim and Scott (2008) proposed an Iteratively Re-weighted Least Squares (IRWLS) algorithm for Robust Kernel Density Estimation (RKDE). …”
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  8. 8
    Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman

    Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman by Mahmudur , Rahman

    Published 2019
    “…At first, appropriate dynamic model is estimated using finite difference method (FDM) and system identification process. …”
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  9. 9
    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization

    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization by Khamis, Alias

    Published 2025
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  10. 10
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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  11. 11
    Improving Photometric Redshifts By Varying Activation Functions In Artificial Neural Networks

    Improving Photometric Redshifts By Varying Activation Functions In Artificial Neural Networks by Pathi, Imdad Binti Mahmud

    Published 2024
    “…The Artificial Neural Network Redshift (annz) algorithm is a fast and simple machine learning photometric redshift estimator. …”
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  12. 12
    Assessing the simulation performances of multiple model selection algorithm

    Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

    Published 2015
    “…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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  13. 13
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
    “…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
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  14. 14
    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment

    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment by Aqel, Mohammad O. A.

    Published 2016
    “…This method is one of the most effective methods for template matching. …”
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  15. 15
    Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation

    Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation by Chang, Jan Voon

    Published 2015
    “…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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  16. 16
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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  17. 17
    Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation

    Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation by Chang, Jan Voon, Ahmad, Idawaty

    Published 2016
    “…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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  18. 18
    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity

    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

    Published 2017
    “…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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  19. 19
    Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems

    Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems by Farzan, Payam, Izadi, Mahdi, Gomes, Chandima, Hesamian, Mohammad Hesam

    Published 2016
    “…The recorded values are evaluated by a designed and tuned multi-layer feed forward neural network and the fault distances from the source are estimated accordingly. In order to highlight the accuracy of the presented method, the scenario is also repeated by recording the peak values of short circuit current which have been mostly used in the published intelligent fault location studies and the obtained results via two different values are compared with each other. …”
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  20. 20
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…In this situation, the existing Elastic-Net and RE-Net methods are not capable of selecting the important variables in the final model. …”
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