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  1. 1
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  2. 2
    A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation

    A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation by Turgut, Mert Sinan, Turgut, Oguz Emrah, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

    Published 2019
    “…First, three different optimization algorithms, namely particle swarm optimization, differential evolution, and whale optimization algorithm, have been applied. …”
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  3. 3
    A filtering algorithm for efficient retrieving of DNA sequence

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…The biologists frequently demand for optimal comparison result so that the perfect structure of living beings evolution can be constructed. …”
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  4. 4
    Automated Student Timetable Scheduling System based on Genetic Algorithm

    Automated Student Timetable Scheduling System based on Genetic Algorithm by Amirul Azuani, Romlee, Noor Ain, Rosly, Meng, Chuan Haw

    Published 2019
    “…Genetic algorithm works based on natural evolutions that comprises of several iterations. …”
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  5. 5
    Analysing ratio-based controllers against motivational game theory in peer-to-peer renewable energy trading

    Analysing ratio-based controllers against motivational game theory in peer-to-peer renewable energy trading by Abdullah Azahari, Abdul Aziz, Mohamad Hanif, Noor Hazrin Hany, Mohamed, Martina Muhaizira

    Published 2024
    “…Yet, the transition from generation to utilization presents challenges, particularly in terms of tracking and matching energy supply with consumer demand. This inefficiency highlights the need for a sophisticated controller equipped with optimal algorithms. …”
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  6. 6
    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
    “…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. …”
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  7. 7
    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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  8. 8
    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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  9. 9
    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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