Search Results - (( a distribution ((svm algorithm) OR (_ algorithm)) ) OR ( parameter estimation model algorithm ))

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    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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    Thesis
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    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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    Article
  4. 4

    Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

    Published 2013
    “…The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. …”
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    Conference or Workshop Item
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    Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

    Published 2018
    “…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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    Thesis
  7. 7

    A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2014
    “…A parametric mixture model of three different distributions is proposed to analyse heterogeneous survival data.The maximum likelihood estimators of the postulated parametric mixture model are estimated by applying an Expectation Maximization Algorithm (EM) scheme.The simulations are performed by generating data, sampled from a population of three component parametric mixture of three different distributions. …”
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    Conference or Workshop Item
  8. 8

    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2013
    “…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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    Article
  9. 9

    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

    Published 2023
    “…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
    Conference Paper
  10. 10

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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    Thesis
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    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. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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  12. 12

    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

    Published 2022
    “…This paper compares different initialization methods and investigates their performance and effects on estimating kinetic parameters’ value in models of biological systems. …”
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    Article
  13. 13

    Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

    Published 2019
    “…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…SVM is a classification technique developed by Vapnik [1] but a practical difficulty of using SVM is the selection of parameters such as C and kernel parameter, � in Gaussian RBF kernel. …”
    Conference Paper
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    Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

    Published 2020
    “…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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    Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop by Ayop, Nor Azura

    Published 2016
    “…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. …”
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    Thesis
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    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). …”
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    Conference or Workshop Item
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    Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain by Mohd Hussain, Mashitah

    Published 2014
    “…First, voltage profile on source distribution system is estimated. The voltage profile is predicted using Independent Component Analysis (lCA) algorithm. …”
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    Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi by Azmi, Aini

    Published 2016
    “…Maximum Likelihood Estimator (MLE) technique is used to fit the best distribution model. …”
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    Article