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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    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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  2. 2
    Neighbour-based on-demand routing algorithms for mobile ad hoc networks

    Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

    Published 2017
    “…This algorithm enhances the network performance, even though the network is experiencing an increase in the number of nodes or traffic load. …”
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  3. 3
    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks

    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    Published 2024
    “…The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). …”
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  4. 4
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. © 2020 by the authors.…”
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  5. 5
    Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms

    Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms by Khudhur, Fadi Hani

    Published 2012
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  6. 6
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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  7. 7
    Performance Comparison of Packet Queuing Algorithm in Wireless Networks

    Performance Comparison of Packet Queuing Algorithm in Wireless Networks by Nor Aida, Mahiddin, Raja Hasyifah, Raja Bongsu, Wan Nor Shuhadah, Wan Nik

    Published 2014
    “…The development in wireless network has changes the fundamental of data communication and networking. …”
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  8. 8
    Performance Comparison of Packet Queuing Algorithm in Wireless Networks

    Performance Comparison of Packet Queuing Algorithm in Wireless Networks by Nor Aida, Mahiddin, Raja Hasyifah, Raja Bongsu, Wan Nor Shuhadah, Wan Nik

    Published 2014
    “…The development in wireless network has changes the fundamental of data communication and networking. …”
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  9. 9
    An Educational Tool Aimed at Learning Metaheuristics

    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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  10. 10
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    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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  11. 11
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    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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  12. 12
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. Policing process drops traffic while shaping process delay traffic to the next time transmissions. …”
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  13. 13
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. Policing process drops traffic while shaping process delay traffic to the next time transmissions. …”
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  14. 14
    DEVELOPMENT OF NODE RELIABILITY DETECTION ALGORITHM FOR WIRELESS SENSOR NETWORKS

    DEVELOPMENT OF NODE RELIABILITY DETECTION ALGORITHM FOR WIRELESS SENSOR NETWORKS by AZMAN, MOHAMAD AFIQ

    Published 2014
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  15. 15
    DEVELOPMENT OF NODE RELIABILITY DETECTION ALGORITHM FOR WIRELESS SENSOR NETWORKS

    DEVELOPMENT OF NODE RELIABILITY DETECTION ALGORITHM FOR WIRELESS SENSOR NETWORKS by AZMAN, MOHAMAD AFIQ

    Published 2014
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  16. 16
    Recognising Malaysia traffic sign with rain drop disturbance using deep learning

    Recognising Malaysia traffic sign with rain drop disturbance using deep learning by Pang, Wan Chee

    Published 2022
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  17. 17
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…The motivation behind the project was to help automate the cumbersome task of validating instruments from images using Convolutional Neural Network (CNNs) algorithm to identify the musical instrument so that this task could be completed with higher accuracy. …”
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  18. 18
    A Grid-Based Reliable Routing (GBRR) protocol for wireless sensor networks

    A Grid-Based Reliable Routing (GBRR) protocol for wireless sensor networks by Jiang, Cailing

    Published 2019
    “…Since the sensors have the characteristics of self-organizing and low cost and the wireless sensor network develops rapidly, more reliable routing algorithms are required to perform better forwarding. …”
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  19. 19
    Congestion management based optimization technique using bee colony

    Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

    Published 2023
    “…The aim of the study is to optimize the cost of generation in power system network within the given available constraints. The study involved the development of bee colony algorithm in addressing congestion management, considering cost optimization as the objective function. …”
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  20. 20
    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study

    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…This study aims to develop a universal artificial neural network model for estimating pressure drop at pipelines under multiphase flow conditions. …”
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