Search Results - (( probable estimation method algorithm ) OR ( data distribution selection algorithm ))

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  1. 1
    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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  2. 2
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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  3. 3
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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  4. 4
    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models

    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

    Published 2004
    “…The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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  5. 5
    Simulation algorithm of bayesian approach for choice-conjoint model

    Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

    Published 2011
    “…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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  6. 6
    Semiparametric inference procedure for the accelarated failure time model with interval-censored data

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

    Published 2019
    “…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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  7. 7
    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model

    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
    Conference Paper
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  8. 8
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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  9. 9
    The research on the signal source number estimation algorithm

    The research on the signal source number estimation algorithm by Peizhi, Wang, Mohamed, Raihani, Mustapha, Norwati, Manshor, Noridayu

    Published 2024
    “…The experimental results show that with the increase of the SNR and the number of array elements, the correct estimation probability of the algorithm also increases correspondingly, which provides a reliable experimental basis and performance evaluation for the estimation. © 2024 Institute of Advanced Engineering and Science. …”
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  10. 10
    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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  11. 11
    Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data

    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
    “…Focus is on modelling the extreme data based on block maxima approach using Gumbel distribution. …”
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  12. 12
    Estimation of transformers health index based on condition parameter factor and hidden Markov model

    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
    “…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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  13. 13
    Static and self-scalable filter range selection algorithms for peer-to-peer networks

    Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

    Published 2011
    “…Two multiple selection algorithm, which are known as “static filter range selection algorithm” and “self-scalable selection algorithm” are proposed. …”
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  14. 14
    Outlier detection in circular regression model using minimum spanning tree method

    Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

    Published 2019
    “…Then, the performances of both algorithms were measured using “success” probability. …”
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  15. 15
    Estimation of unemployement in Malaysia using fourth-order taylor’s series method and fourthorder runge kutta method / Nur Batrisyia Suhaimi

    Estimation of unemployement in Malaysia using fourth-order taylor’s series method and fourthorder runge kutta method / Nur Batrisyia Suhaimi by Suhaimi, Nur Batrisyia

    Published 2021
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  16. 16
    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin

    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

    Published 2021
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  17. 17
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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  18. 18
    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching

    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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  19. 19
    Statistical fixed range multiple selection algorithm for peer-to-peer system

    Statistical fixed range multiple selection algorithm for peer-to-peer system by Kweh, Yeah Lun, Othman, Mohamed, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2010
    “…In this research, a new multiple selection algorithm, which is known as "statistical fixed range multiple selection algorithm" is proposed. …”
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  20. 20
    Static range multiple selection algorithm for peer-to-peer system

    Static range multiple selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2011
    “…In this research, a new multiple selection algorithm, which is known as "static range statistical multiple selection algorithm" is proposed. …”
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