Search Results - (( data replication using algorithm ) OR ( model classification using algorithm ))

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  1. 1

    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
    “…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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    Article
  2. 2

    Relationship based replication algorithm for data grid by Yusof, Yuhanis

    Published 2014
    “…The Relationship based Replication algorithm aims to improve the Data Grid performance by reducing the job execution time, bandwidth and storage usage.The RBR was realized using a network simulation (OptorSim) and experiment results revealed that it offers better performance than existing replication algorithms.…”
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    Monograph
  3. 3

    Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor by Terence Jerome Daim

    Published 2023
    “…The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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    Thesis
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    Managing Fragmented Database Using BVAGQ-AR Replication Model by Ainul Azila, Che Fauzi, Noraziah, Ahmad, Tutut, Herawan, Z., Abdullah, Gupta, Ritu

    Published 2017
    “…Problem arises when the database is packed with data, but it has lacked of knowledge. If the unreasonable data is used in database replication, it will cause waste of data storage and delay the time taken for a replication process. …”
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    Article
  6. 6

    Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Herawan, Tutut, Zailani, Abdullah

    Published 2015
    “…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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    Article
  7. 7

    Managing MyGRANTS Fragmented Database Using Binary Vote Assignment Grid Quorum with Association Rule (BVAGQ-AR) Replication Model by Noraziah, Ahmad, Wan Maseri, Wan Mohd, Ainul Azila, Che Fauzi

    Published 2015
    “…Nevertheless, if the impractical data is used in database replication, this will cause waste of data storage and the time taken for a replication process will be delayed. …”
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    Conference or Workshop Item
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    Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

    Published 2008
    “…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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    Book Section
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  12. 12

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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    Article
  13. 13
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    A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

    Published 2012
    “…The use of three to five transactions is in NRG the data will be replicated into three to five sites. …”
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    Thesis
  15. 15

    BVAGQ-AR for Fragmented Database Replication Management by N., Ahmad, Ainul Azila, Che Fauzi, Sharifah Hafizah, Sy Ahmad Ubaidillah, Al-Kazemi, Basem, Odili, Julius Beneoluchi

    Published 2021
    “…Although we have been packed with data, we still have lacked of knowledge. Nevertheless, if the impractical data is used in database replication, this will cause waste of data storage and the time taken for a replication process will be delayed. …”
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    Article
  16. 16

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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    Article
  17. 17

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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    Thesis
  18. 18

    Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

    Published 2021
    “…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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    Student Project
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    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
  20. 20

    Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

    Published 2015
    “…In assessing the result, the Lazy model using K Star algorithm was the best classification model among the five models had the most outstanding accuracy of 86.67%. …”
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    Article