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  1. 1
    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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  2. 2
    An evolutionary based features construction methods for data summarization approach

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…This research addresses the question whether a data summarization approach can be utilized to predict the survival of Coral Reefs in Malaysia by identifying the survival factors for these Coral Reefs. A data summarization approach is proposed due to its capability to learn data stored in multiple tables. …”
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  3. 3
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
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  4. 4
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…The “ensemble” model selected here to achieve better predictive performance, is used to predict future market price. The proposed approachoutperforms existing available meta-heuristic algorithms. …”
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  5. 5
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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  6. 6
    A review: Use of evolutionary algorithm for optimisation of machining parameters

    A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

    Published 2021
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  7. 7
    Towards Software Product Lines Optimization Using Evolutionary Algorithms

    Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

    Published 2019
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  8. 8
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  9. 9
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Evolutionary computation (EC) is a method that is ubiquitously used to solve complex computation. …”
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  10. 10
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  11. 11
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  12. 12
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  13. 13
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  14. 14
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  15. 15
    PID Tuning Of Process Plant Using Evolutionary Algorithm

    PID Tuning Of Process Plant Using Evolutionary Algorithm by Guong, Robert Ling Leh

    Published 2014
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    Final Year Project
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  16. 16
    Application of genetic algorithm and JFugue in an evolutionary music generator

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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  17. 17
    Maintain optimal configurations for large configurable systems using multi-objective optimization

    Maintain optimal configurations for large configurable systems using multi-objective optimization by Jamil, Muhammad Abid, Alsadie, Deafallah, Nour, Mohamed K., Awang Abu Bakar, Normi Sham

    Published 2022
    “…The proposed approach is also used to generate the optimized test suites with the help of different multi-objective Evolutionary Algorithms (MOEAs).…”
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  18. 18
    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry

    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

    Published 2014
    “…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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  19. 19
    A Systematic Exploration of Mutation Space in a Hybridized Interactive Evolutionary Programming for Mobile Game Programming

    A Systematic Exploration of Mutation Space in a Hybridized Interactive Evolutionary Programming for Mobile Game Programming by Jia Hui Ong, Jason Teo

    Published 2014
    “…Evolutionary programming is the core Evolutionary Algorithm (EA) used in this study where it is hybridized with Interactive Evolutionary Algorithm (IEA) to generate different rulesets that was played on a custom arcade-type mobile game. …”
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  20. 20
    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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