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  1. 1
    Academic leadership bio-inspired classification model using negative selection algorithm

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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  2. 2
    Statistical process control for failure crushing time data using competing risks model.

    Statistical process control for failure crushing time data using competing risks model. by Elfaki, F.A.M., Daud, Isa, Ibrahim, Noor Akma, Daud, J., Azram, M., Usman, M.

    Published 2011
    “…EM algorithm method is used to estimate the parameter of the model. …”
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  3. 3
    Statistical process control for failure crushing time data using competing risks model

    Statistical process control for failure crushing time data using competing risks model by Elfaki, Faiz Ahmed Mohamed, Daoud, Jamal Ibrahim, Azram, Mohammad, Daud, Isa, Ibrahim, N.A., Usman, Mustofa

    Published 2011
    “…EM algorithm method is used to estimate the parameter of the model. …”
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  4. 4
    Competing risks for reliability analysis using Cox’s model

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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  5. 5
    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
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  6. 6
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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  7. 7
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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  8. 8
    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm

    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm by Yifan, Bai, Kamarudin, Khairul Manami, Alli, Hassan

    Published 2024
    “…Afterward, a mathematical version is used to symbolize the layout preference problems, and the layout scheme selection method is simulated. …”
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  9. 9
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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  10. 10
    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…Data containing eleven predictive variables was used to train and test neural network model. The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. …”
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  11. 11
    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…Residual-based approaches are used to assess the validity of the two models (MW, CC) assumptions. …”
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  12. 12
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…In a conventional competing risk s model, the time to failure of a particular experimental unit might be censored and the cause of failure can be known or unknown. …”
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  13. 13
    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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  14. 14
    Spiral-sooty tern optimization algorithm for dynamic modelling of a twin rotor system

    Spiral-sooty tern optimization algorithm for dynamic modelling of a twin rotor system by Ahmad Nor Kasruddin, Nasir, Mohd Falfazli, Mat Jusof, Mohd Redzuan, Ahmad, Addie Irawan, Hashim

    Published 2022
    “…A spiral model is incorporated into the Sooty-Tern Optimization Algorithm (STOA) structure. …”
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  15. 15
    Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm

    Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Jianghua Yin, Jianghua Yin, Guodong Ma, Guodong Ma

    Published 2023
    “…Wavelength selection is crucial to the success of near-infrared (NIR) spectroscopy analysis as it considerably improves the generalization of the multivariate model and reduces model complexity. This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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  16. 16
    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
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  17. 17
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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  18. 18
    Competence-Oriented Decision Model for Optimizing the Operation of a Cascading Hydroelectric Power Reservoir

    Competence-Oriented Decision Model for Optimizing the Operation of a Cascading Hydroelectric Power Reservoir by Asfaw, Tilahun Derib, Wan Yusof, Khamaruzaman, Hashim, Ahmad Mustafa

    Published 2013
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  19. 19
    Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir

    Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir by Mohammad Nasir, Khairun Nisa

    Published 2024
    “…As a result, this study has achieved 89.82% from the 80-20 split using CNN algorithm with an F1 score of 88.08%. The research then goes on to assess how well the CNN model generalizes to various agricultural environments that support multiple crop situations. …”
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  20. 20
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…The segmentation of brain MRI images is a challenging and complex task, due to noise and inhomogeneity. The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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