Search Results - (( simulation classification means algorithm ) OR ( java implementation mining 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

    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka by Zainal K., Sulaiman N.F., Jali M.Z.

    Published 2024
    “…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
    Article
  7. 7

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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    Thesis
  8. 8

    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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    Article
  9. 9

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. …”
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    Thesis
  10. 10

    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
  11. 11

    Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim by Mohamad Kasim, Adibah I’zzah

    Published 2025
    “…The classification process incorporated Root Mean Square (RMS) analysis for feature extraction and multilayer perceptron (MLP) neural networks for pattern recognition. …”
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    Thesis
  12. 12
  13. 13

    An efficient likelihood-based modulation classification algorithm for multiple-input multiple-output systems by Bahloul, M.R., Yusoff, M.Z., Abdel-Aty, A.-H., Saad, M.N.M.

    Published 2016
    “…This can be performed by employing a Modulation Classification (MC) algorithm, which can be feature-based or likelihood-based. …”
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    Article
  14. 14

    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

    Published 2016
    “…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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    Article
  15. 15

    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
  16. 16

    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

    Published 2016
    “…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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    Article
  17. 17

    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
    “…The simulation results show that the highest improvement of H-BFGS in terms of generalisation accuracy is on the Voice Gender classification with 43.33% improvement for 60:40 data division. …”
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    Thesis
  18. 18

    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

    Published 2007
    “…This paper presents the need for such a prediction and optimization engine that discusses the approach for history-based prediction and optimization. Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

    Published 2015
    “…To overcome these problems this project proposes a methodology for determining consumers’ TLPs by using fuzzy C-means (FCM) clustering method and probability neural networks (PNN) classification techniques. …”
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    Thesis