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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
    “…Generally in Choice-Conjoint method the Multinomial Logit Model (MNL) is normally used to analyze choice conjoint data, but the MNL has some serious limitations. …”
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  2. 2
    Tree-based contrast subspace mining method

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

    Published 2020
    “…The research works involve first preparing the real world numerical and categorical data sets. 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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  3. 3
    New entropy-based method for gene selection

    New entropy-based method for gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2009
    “…In this paper, we use Shannon theorem and penalized logistic regression (PLR) as a probability estimator to present a new algorithm for dimension reduction and collect a subset of representative genes of gene expression profile. …”
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  4. 4
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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  5. 5
    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation

    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation by Din, Abdul Sattar

    Published 2013
    “…These two observation data are tested using their signs before one of them with the highest probability of giving a positive update is selected to be used for position update. …”
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  6. 6
    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
    “…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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  7. 7
    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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  8. 8
    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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  9. 9
    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…For this purpose, the most probable location of incoming instance for each class is estimated. …”
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  10. 10
    A framework for automatic modelling of survival using fuzzy inference.

    A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

    Published 2012
    “…After the initialisation of the fuzzy inference structure, the replication data (until time to event) will be subject to be trained using the gradient descent and nonnegative least square algorithm to estimate the conditional event probability. …”
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  11. 11
    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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  12. 12
    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
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  13. 13
    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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  14. 14
    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
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  15. 15
    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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  16. 16
    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah

    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

    Published 2022
    “…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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