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  1. 1
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
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  2. 2
    A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions

    A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions by Syaripudin, Undang

    Published 2025
    “…There are several stages in developing a KMS, namely compiling data requirements for the four lecturer competencies: pedagogical competency, professional competency, personality competency, and social competency. …”
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  3. 3
    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment

    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment by Saeed, Gamil Abdulraqeb Abdullah, Chuan, Zun Liang, Roslinazairimah, Zakaria, Wan Nur Syahidah, Wan Yusoff

    Published 2016
    “…Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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  4. 4
    Determination of the best single imputation algorithm for missing rainfall data treatment

    Determination of the best single imputation algorithm for missing rainfall data treatment by Gamil Abdulraqeb Abdullah Saeed, Chuan, Zun Liang, Roslinazairimah Zakaria, Wan Nur Syahidah Wan Yusoff, Mohd Zuki Salleh

    Published 2016
    “…Consequently, a competent imputation algorithm for missing data treatment algorithm is very much needed. …”
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  5. 5
    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
    “…In the experimental phase, academic leadership competency data were collected from a selected higher learning institution as training data-set based on 10-fold cross validation. …”
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  6. 6
    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
    “…This paper describes a Statistical Process Control (SPC) for failure crushing time data using competing risks model. …”
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  7. 7
    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
    “…This paper describes a Statistical Process Control (SPC) for failure crushing time data using competing risks model. …”
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  8. 8
    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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  9. 9
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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  10. 10
    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
    “…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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  11. 11
    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
    “…Also, the modification of the two models showed better results compared with Crowder et al., especially for the second causes of failure. Originality/value – A modification of the two competing risk models has mostly been applied in failure time data and simulation data. …”
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  12. 12
    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
    “…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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  13. 13
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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  14. 14
    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
    “…This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. …”
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  15. 15
    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
    “…A good model is a model that encapsulates the initial process and therefore represents a close estimate to the true model that generated the data.However, whenever there is more than one model to be considered, selection decision needs to be based on its competence to generalize, which is defined as a model’s ability to fit not only current data but also to forecast future data. …”
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  16. 16
    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants

    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

    Published 2019
    “…The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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  17. 17
    A Penalty-Based Genetic Algorithm For The Composite Saas Placement Problem In The Cloud

    A Penalty-Based Genetic Algorithm For The Composite Saas Placement Problem In The Cloud by Mohd Yusoh, Zeratul Izzah, Tong, Maolin

    Published 2010
    “…Cloud computing is a latest new computing paradigm where applications, data and IT services, are provided over the Internet. …”
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  18. 18
    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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  19. 19
    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
    “…The data entered online using web as a medium and then executing back propagation simulation to obtain the desired neural network model, and to predict information technology competency based on the model obtained. …”
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  20. 20
    Assessing the level of competence in automated trading among Malaysian traders

    Assessing the level of competence in automated trading among Malaysian traders by Zarith Sofia, Zulkifli, Hairuddin, Mohammad, Miswan, Surip, Nurnadiah, Zamri, Mustafa, Mamat, Sahimel Azwal, Sulaiman

    Published 2023
    “…The objective of this research is to figure out the level of competence that Malaysian retail traders have in Automated or Algorithmic Trading (AT) focusing on currency trading. …”
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