Search Results - (( java implementation learning algorithm ) OR ( pattern making process 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

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…Classification and patterns extraction from customer data is very important for business support and decision making. …”
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    Citation Index Journal
  3. 3

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

    Published 2011
    “…decision making. Timely identification of newly emerging trends is needed in business process. …”
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    Citation Index Journal
  4. 4

    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
  5. 5

    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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    Thesis
  6. 6

    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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    Thesis
  7. 7

    Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

    Published 2009
    “…Patterns and classification of stock or inventory data is very important for business support and decision making. …”
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    Conference or Workshop Item
  8. 8

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In a real world, pattern recognition problems in diversified forms are ubiquitous and are critical in most human decision making tasks. …”
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    Thesis
  9. 9

    Algorithms for frequent itemset mining: a literature review by Chee, C.-H., Jaafar, J., Aziz, I.A., Hasan, M.H., Yeoh, W.

    Published 2018
    “…Data Analytics plays an important role in the decision making process. Insights from such pattern analysis offer vast benefits, including increased revenue, cost cutting, and improved competitive advantage. …”
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    Article
  10. 10

    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
  11. 11

    Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

    Published 1998
    “…The main intend of the system was to verify if the marking can be read by humans. Algorithms that the current process uses however, was not capable in handling mark variations that was introduced by the marking process. …”
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    Thesis
  12. 12

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    “…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
    Conference paper
  13. 13

    Coronary artery segmentation in angiograms with pattern recognition techniques - a survey by Tayebi, Rohollah Moosavi, Sulaiman, Puteri Suhaiza, O. K. Rahmat, Rahmita Wirza, Dimon, Mohd Zamrin, Kadiman, Suhaini, Abdullah, Lilly Nurliyana, Mazaheri, Samaneh

    Published 2013
    “…Coronary artery segmentation algorithm in angiograms is a fundamental component of each cardiac image processing system. …”
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    Conference or Workshop Item
  14. 14

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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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

    Object with symmetrical pattern recognition with dynamic size filter by Syed Mohamad Shazali, Syed Abdul Hamid, Mohd Aras, Mohd Shahrieel, Abdul Azis, Fadilah, Ali, Fara Ashikin, Anuar , Mohamed Kassim

    Published 2011
    “…This paper presents the implementation of object with symmetrical pattern recognition algorithm for 2D vision system of 3D vision-based multi sensor feedback system. …”
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    Conference or Workshop Item
  17. 17

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Therefore, there is a strong need to automate this process. Such automated systems must rely on robust and effective algorithms for detection and prediction. …”
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    Article
  18. 18

    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

    Published 2006
    “…Data mining can discover patterns or rules from a vast volume of data. This patterns or rules may help to develop better decision-making process. …”
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    Conference or Workshop Item
  19. 19

    Mobility Management Incorporating Pattern Recognition in the Handoff Decision by Kwong, C.F., Lee, S.W., Sim, M.L.

    Published 2009
    “…This paper will discuss different techniques in the traditional handover decision algorithm and explore the method of handoff decision using pattern recognition method, mainly the Adaptive Network Fuzzy Inference System (ANFIS). …”
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    Book Section
  20. 20

    A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

    Published 2023
    “…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
    Article