Search Results - (( java implementation some algorithm ) OR ( variables classification _ algorithm ))

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  1. 1

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis
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    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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    Thesis
  4. 4

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
  5. 5

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…The average classification accuracies for the ACOR-SVM, IACOR-SVM, ACOMV-R and IACOMV-R algorithms are 94.73%, 95.86%, 97.37% and 98.1% respectively. …”
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    Thesis
  6. 6

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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    Conference or Workshop Item
  7. 7

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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    Conference or Workshop Item
  8. 8

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  9. 9

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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    Article
  10. 10

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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    Undergraduate Final Project Report
  11. 11

    Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…Experimental results obtained from the proposed algorithm are better compared with other approaches in terms of classification accuracy and feature subset selection.…”
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    Article
  12. 12

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Article
  13. 13

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
  14. 14

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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    Article
  15. 15

    Implementation of RIO in UMJaNetSim / Chan Chin We by Chan, Chin We

    Published 2004
    “…In this project, I will do some research on the recent TCP congestion control and avoidance mechanisms and implement one of the mechanisms into the Java Network Simulator (JaNetSim). …”
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    Thesis
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    Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm by Liu, Jingrui, Pan, Dongyang

    Published 2019
    “…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
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    Article
  17. 17

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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    Conference or Workshop Item
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    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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    Article
  20. 20

    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

    Published 2025
    “…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
    Article