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  1. 1
    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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  2. 2
    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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  3. 3
    Bayesian inference for the bivariate extreme model

    Bayesian inference for the bivariate extreme model by Mohd Amin, Nor Azrita, Adam, Mohd Bakri

    Published 2016
    “…Using simulation study, the capability of MTM algorithm to analyze the posterior distribution is implement. …”
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  4. 4
    Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data

    Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data by Rostami, Mohammad

    Published 2016
    “…In this research, application of extreme value theory within a Bayesian framework using the Metropolis Hastings algorithm and the slice sampler algorithm as an alternative approach, has been introduced. …”
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  5. 5
    Adaptive framed pseudo-Bayesian Aloha algorithm with priorities

    Adaptive framed pseudo-Bayesian Aloha algorithm with priorities by Habaebi, Mohamed Hadi, Mohd Ali, Borhanuddin

    Published 2000
    “…A new wireless framed pseudo-bayesian Aloha algorithm with adaptive priorities, for wireless ATM reservation-based TDMA MAC prolocols, is presented. …”
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  6. 6
    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications

    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

    Published 2022
    “…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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  7. 7
    Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images

    Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images by Farzan, Ali, Ramli, Abdul Rahman, Mashohor, Syamsiah, Mahmud, Rozi

    Published 2010
    “…Hence involving problem specific information and expert knowledge in designing segmentation algorithms seems to be useful. A two-fold fuzzy segmentation algorithm based on Bayesian method is proposed in this paper. …”
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  8. 8
    Extreme air pollutant data analysis using classical and Bayesian approaches

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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  9. 9
    A bayesian via laplace approximation on log-gamma model with censored data

    A bayesian via laplace approximation on log-gamma model with censored data by Yusuf, Madaki Umar, Abu Bakar, Mohd Rizam, Husain, Qasim Nasir, Ibrahim, Noor Akma, Arasan, Jayanthi

    Published 2016
    “…Methods/Analysis: Alternatively, Bayesian estimation by MCMC simulation using the Random-walk Metropolis algorithm was applied, using AIC and BIC comparison makes it the smallest and great choice for fitting the survival models and simulations by Markov Chain Monte Carlo Methods. …”
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  10. 10
    Slice sampling technique in Bayesian extreme of gold price modelling

    Slice sampling technique in Bayesian extreme of gold price modelling by Rostami, Mohammad, Adam, Mohd Bakri, Ibrahim, Noor Akma, Yahya, Mohamed Hisham

    Published 2013
    “…In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. …”
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  11. 11
    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka

    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka by Zainal K., Sulaiman N.F., Jali M.Z.

    Published 2024
    “…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
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  12. 12
    A new indoor localization system based on Bayesian graphical model

    A new indoor localization system based on Bayesian graphical model by Alhammadi, Abdulraqeb, Hashim, Fazirulhisyam, A. Rasid, Mohd Fadlee, Alraih, Saddam

    Published 2017
    “…The proposed Bayesian model was simulated using OpenBUGS, a graphical user interface. …”
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  13. 13
    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
    “…Mean squared error (MSE) and absolute bias are obtained and used to compare the Bayesian and the maximum likelihood estimation through simulation studies. …”
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  14. 14
    E4ML: Educational Tool for Machine Learning

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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  15. 15
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  16. 16
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  17. 17
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  18. 18
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…Performance analysis was achieved using simulated and eighteen real-life classification and regression microarray cancer datasets. …”
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  19. 19
    Variational Bayesian inference for exponentiated Weibull right censored survival data

    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
    “…The AFT model was developed using two comparative studies based on real-life and simulated data sets. …”
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  20. 20
    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun

    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

    Published 2021
    “…A Bayesian method for CNN using TensorFlow Probability was used in this study. …”
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