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  1. 1
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  2. 2
    Prevention And Detection Mechanism For Security In Passive Rfid System

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…A GUI is created in a form of JAVA application to display data detected from tag. …”
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  3. 3
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…Validation was conducted through three experiments involving four Java programs. The results demonstrated high effectiveness, with scores ranging from 93.91% to 99.51% on the scaled weighted average percentage of faults detected (APFD) metric. …”
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  4. 4
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  5. 5
    Automatic generation of content security policy to mitigate cross site scripting

    Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

    Published 2016
    “…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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  6. 6
    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor

    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

    Published 2017
    “…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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  7. 7
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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  8. 8
    Challenges of hidden data in the unused area two within executable files

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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