Search Results - (( java implementation mining algorithm ) OR ( program selection models algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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    Article
  3. 3

    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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    Conference or Workshop Item
  4. 4

    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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    Conference or Workshop Item
  5. 5

    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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    Final Year Project / Dissertation / Thesis
  6. 6

    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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    Thesis
  7. 7

    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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    Thesis
  8. 8

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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    Article
  9. 9

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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    Article
  10. 10

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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    Article
  11. 11

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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    Article
  12. 12
  13. 13

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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    Thesis
  14. 14
  15. 15

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
  16. 16

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
  17. 17

    IP algorithms in compact rough classification modeling by Bakar, Azuraliza Abu, Sulaiman, Md Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2001
    “…The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. …”
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    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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    Thesis
  20. 20

    Development of decentralized data fusion algorithm with optimized kalman filter. by Quadri, Sayed Abulhasan

    Published 2016
    “…This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. …”
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    Thesis