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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    An empirical study of density and distribution functions for ant swarm optimized rough reducts

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…The density and distribution functions are two common types of Gaussian distribution representation. …”
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  8. 8
    Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks

    Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks by Ali, A., Nor, N.M., Ibrahim, T., Romlie, M.F., Bingi, K.

    Published 2021
    “…To deal the stochastic behavior of solar irradiance, 15 years of weather data is modeled by using beta probability density function (Beta-PDF). The proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired for different time varying voltage dependent load models. …”
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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    A new HMCR parameter of harmony search for better exploration

    A new HMCR parameter of harmony search for better exploration by Mansor, N.F., Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S.

    Published 2016
    “…This research focuses on the HMCR parameter adjustment strategy using step function with combined Gaussian distribution function to enhance the global optimality of HS. …”
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  14. 14
    A new HMCR parameter of harmony search for better exploration

    A new HMCR parameter of harmony search for better exploration by Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S

    Published 2015
    “…This research focuses on the HMCR parameter adjustment strategy using step function with combined Gaussian distribution function to enhance the global optimality of HS. …”
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  15. 15
    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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  16. 16
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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  17. 17
    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…Therefore, there are various algorithms that could be applied in order to integrate distribution generation units into the distribution network. …”
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  18. 18
    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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  19. 19
    Optimal multiple distributed generation output through rank evolutionary particle swarm optimization

    Optimal multiple distributed generation output through rank evolutionary particle swarm optimization by Jamian, J.J., Mustafa, M.W., Mokhlis, Hazlie

    Published 2015
    “…Moreover, the local best (P-best) and global best (G(best)) values are obtained in simplify manner in the REPSO algorithm. …”
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  20. 20
    Chaos search in fourire amplitude sensitivity test

    Chaos search in fourire amplitude sensitivity test by Koda, Masato

    Published 2012
    “…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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