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  1. 1

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  2. 2

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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  3. 3

    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

    Published 2013
    “…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
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  4. 4

    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…Therefore, this study aims to solve the feature selection problem using binary particle swarm optimization (BPSO). …”
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  5. 5

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation. …”
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  6. 6

    A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham

    Published 2018
    “…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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  7. 7

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  8. 8

    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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  9. 9

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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  10. 10

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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  11. 11

    Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations by Goheannee

    Published 2014
    “…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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  12. 12

    Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution by Mohamed, Mohd Rezal

    Published 2019
    “…From the results obtained, the Analytical Sub-Domain Differential Evolution Algorithm (ASDEA) has better optimization technique capability compared with Analytical Sub-Domain Particle Swarm Optimization (ASPSO). …”
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  13. 13

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  14. 14

    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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  15. 15
  16. 16

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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  17. 17

    Voltage constrained optimal power flow based using genetic algorithm by Yassir Asnawi, Teuku Hasannuddin

    Published 2015
    “…Effectiveness of the proposed method was tested on IEEE 30 bus system and it has been compared to other optimization of power fl ow using other methods, for example the Evolutionary Programming (EP), Differential Evolution (DE) and Particle Swarm Optimization (PSO) methods. …”
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  18. 18

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
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  19. 19

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…The results are compared to other NIC methods, i.e., Particle Swarm Optimization (PSO) and Differential Evolution (DE), in which AFSA gives better accuracy with feasible performance for all datasets.…”
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  20. 20

    Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

    Published 2023
    “…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
    Article