Search Results - (( developing rule selection algorithm ) OR ( java implementation learning 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
  2. 2

    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection by Wong, S.V, Hamouda, A.M.S

    Published 2002
    “…The authors have developed fuzzy models for machinability data selection (Int. …”
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    Article
  3. 3

    Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach by Wong, Shaw Voon, Salem Hamouda, Abdel Magid

    Published 2001
    “…Genetic optimization is suggested in this paper to further optimizing the fuzzy rules optimization with genetic algorithms has been developed. …”
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    Article
  4. 4

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…Finally, after the aspects list was obtained from the selected rules, a pruning algorithm (PA) is developed to remove the incorrect aspects and retain the correct aspects. …”
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    Thesis
  5. 5
  6. 6

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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    Conference or Workshop Item
  7. 7

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  8. 8

    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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  9. 9

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

    Published 2017
    “…This study proposed and focused on the development of a prototype that uses the Negative Selection Algorithm to classify the input image whether it is belongs to melanoma skin cancer or benign mole. …”
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  12. 12

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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    Article
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    Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions by Tze, Ling Jee, Kok, Chin Chai, Kai, Meng Tay, Chee, Peng Lim

    Published 2014
    “…The Non-Dominated Sorting Genetic Algorithms-II (NSGA-II) is adopted for fuzzy rule selection, in accordance with the Pareto optimal criterion. …”
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    Proceeding
  15. 15

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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  16. 16

    Comprehensive power restoration approach using rule-based method for 11kV distribution network by Khalid A.R., Ahmad S.M.S., Shakil A., Pa N.N., Shafie R.M.

    Published 2023
    “…This paper presents a restoration algorithm based on a Rule-Based approach. The algorithm is computationally programmed to provide multiple solutions and to recommend the best option of switching for a dispatcher. …”
    Conference Paper
  17. 17

    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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  18. 18

    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    Published 2014
    “…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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    Conference or Workshop Item
  19. 19

    A rough-fuzzy inference system for selecting team leader for software development teams by Jaafar, Jafreezal, Gilal, Abdul Rehman, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin, Hasan, Mohd Hilmi

    Published 2017
    “…Moreover, the model development was divided into two portions: Decision Rules Development and Fuzzy Inference System (FIS) development. …”
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    Book Section
  20. 20

    A Rough-Fuzzy Inference System for Selecting Team Leader for Software Development Teams by Jaafar, J., Gilal, A.R., Omar, M., Basri, S., Aziz, I.A., Hasan, M.H.

    Published 2018
    “…Moreover, the model development was divided into two portions: Decision Rules Development and Fuzzy Inference System (FIS) development. …”
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    Article