Search Results - (( data replication testing algorithm ) OR ( variable estimation mining algorithm ))

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  1. 1
    Expectation maximization clustering algorithm for user modeling in web usage mining system

    Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

    Published 2009
    “…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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  2. 2
    A novel deadlock detection algorithm for neighbour replication on grid environment

    A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

    Published 2012
    “…The aim of this research is to handle the deadlock problem in NRG to preserve the consistency of data and increase the throughput. The NRGDD simulation model has been developed to test the algorithm on NRG. …”
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  3. 3
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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  4. 4
    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions

    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Wendy Ling, Shinyie, Tan Lit, Ken

    Published 2022
    “…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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  5. 5
    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions

    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Soo, Fen Fam, Wendy, Ling Shinyie, Tan, Lit Ken

    Published 2022
    “…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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  6. 6
    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions

    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Shinyie, Wendy Ling, Ken, Tan Lit

    Published 2022
    “…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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  7. 7
    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions

    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Fam, Soo Fen, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Wendy, Ling Shinyie, Tan, Lit Ken

    Published 2022
    “…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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  8. 8
    Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman

    Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

    Published 2021
    “…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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  9. 9
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

    Published 2018
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  10. 10
    Finite element modeling and updating for dynamic study of exhaust structure

    Finite element modeling and updating for dynamic study of exhaust structure by M. S. M., Fouzi, M. S. M., Sani

    Published 2020
    “…Hence, this paper is carried out to reduce the discrepancies between numerical prediction results with measured test data on FE model of exhaust structure by implementing FE model updating using SOL200 algorithm. …”
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  11. 11
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

    Published 2018
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  12. 12
    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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  13. 13
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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  14. 14
    Enhancing clustering algorithm with initial centroids in tool wear region recognition

    Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

    Published 2020
    “…K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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  15. 15
    Identification of debris flow initiation zones using topographic model and airborne laser scanning data

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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  16. 16
    Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices

    Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices by Sheikh, Abdul Manan, Islam, Md. Rafiqul, Habaebi, Mohamed Hadi, Zabidi, Suriza Ahmad, Najeeb, Athaur Rahman, Baloch, Mazhar

    Published 2026
    “…The NIST statistical test suite was applied to the CRP data of the RO PUF to evaluate its randomness quality. …”
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  17. 17
    A self-adaptive agent-based simulation modelling framework for dynamic processes

    A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

    Published 2023
    “…Case studies for simulating dynamic processes of new student registration (administrative domain), transport request (transportation domain) and crime investigation (security domain) with real data collected through interview and document reviews to test the proposed idea. …”
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  18. 18
    Finger-Vein Biometric Identification Using Convolutional Neural Network

    Finger-Vein Biometric Identification Using Convolutional Neural Network by Syafeeza, Ahmad Radzi, Mohamed, Khalil-Hani, Rabia, Bakhteri

    Published 2016
    “…An identification rate of 100.00% is achieved, with an 80/20 percent ratio for separation of training and test samples, respectively. An additional number of subjects have also been tested, in which for 81 subjects an accuracy of 99.38% is achieved.…”
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  19. 19
    Access control model based on trust, purpose, and role in materialized view for privacy protection

    Access control model based on trust, purpose, and role in materialized view for privacy protection by Salji, Mohd Rafiz

    Published 2019
    “…This study focuses on data privacy protection in materialized view. Materialized view is a replica of a table which is created in a very large system where data are replicated from the master tables. …”
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  20. 20
    Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model

    Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model by Norhaida, Binti Hussain, Wai Shiang, Cheah, Wai Loke, Seng

    Published 2025
    “…In addition, simulated data can overcome the lack of genuine datasets for specific crowd situations. …”
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