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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  8. 8
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…Based on the findings, Algorithm 2 outperforms Algorithm 1 in classifying the minority group, while both proposed algorithms perform equally well in classifying the majority group. …”
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  9. 9
    BASE: a bacteria foraging algorithm for cell formation with sequence data

    BASE: a bacteria foraging algorithm for cell formation with sequence data by Nouri, Hossein, Tang, Sai Hong, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar

    Published 2010
    “…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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  10. 10
    An optimal tasks scheduling algorithm based on QoS in cloud computing network

    An optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen Mohammed Abdo

    Published 2017
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  11. 11
    Customer segmentation on clustering algorithms

    Customer segmentation on clustering algorithms by Toh, Wei Xuan

    Published 2023
    “…The aim of the study is to identify customer groups based on their buying behaviour and demographic characteristics. …”
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  12. 12
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  13. 13
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…Several simulated systems and real-world timedependent data, are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  14. 14
    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group

    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group by Azali Saudi, Jumat Sulaiman

    Published 2014
    “…It is inspired by the behaviour-based paradigm approach to robotics architecture, in which the searching algorithm employs Laplacian Behaviour-Based Control (LBBC) during space exploration of the environment. …”
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  15. 15
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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  16. 16
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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  17. 17
    Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering

    Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering by Umelo, Nnamdi Henry, Noordin, Nor Kamariah, A. Rasid, Mohd Fadlee, Tan, Kim Geok, Hashim, Fazirulhisyam

    Published 2023
    “…Variants of the proposed kg-DFSA, traditional DFSA and another grouping based DFSA algorithm (FCM-DFSA) were implemented in MATLAB. …”
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  18. 18
    A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali

    A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali by Hilyati Hanina, Zazali

    Published 2012
    “…The algorithms work by arranging parameters using finite field group in elliptic curve E. …”
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  19. 19
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  20. 20
    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms

    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

    Published 2014
    “…This study explores the performance accuracies of partitioning-based algorithms and probabilistic model-based algorithm. …”
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