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  1. 1
    Metaheuristic Algorithms and Neural Networks in Hydrology

    Metaheuristic Algorithms and Neural Networks in Hydrology

    Published 2024
    “…It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.…”
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  2. 2
    Review of Multi-Objective Swarm Intelligence Optimization Algorithms

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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  3. 3
    Task scheduling in cloud computing using Harris-Hawk Optimization

    Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

    Published 2024
    “…In this study, the proposed HHO algorithm is simulated and compared with other well-known swarm intelligence algorithms, including Bat Algorithm (BA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). …”
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  4. 4
    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation

    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation by Mohd Yusof, Norfadzlia, Muda, Azah Kamilah, Pratama, Satrya Fajri, Abraham, Ajith

    Published 2022
    “…In addition, statistical significance tests are also conducted using the Friedman test and Wilcoxon signed-rank test. The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
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  5. 5
    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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  6. 6
    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm

    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

    Published 2023
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  7. 7
    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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  8. 8
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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  9. 9
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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  10. 10
    The Implementation of Genetic Algorithm in Path Optimization

    The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

    Published 2005
    “…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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  11. 11
    Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin

    Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin by Sariff, Nohaidda, Buniyamin, Norlida

    Published 2010
    “…This paper presents the application of Genetic Algorithm and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. …”
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  12. 12
    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition

    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

    Published 2024
    “…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”
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  13. 13
    The effect of GA parameters on the performance of GA-based QoS routing algorithm

    The effect of GA parameters on the performance of GA-based QoS routing algorithm by Yussof S., See O.H.

    Published 2023
    “…Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. …”
    Conference paper
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  14. 14
    Minimization of tool path length of drilling process using particle swarm optimization (PSO)

    Minimization of tool path length of drilling process using particle swarm optimization (PSO) by Abdullah, Haslina, Zaman, Nizam Nurehsan, Talib, Norfazillah, Lee, Woon Kiow, Saleh, Aslinda, Zakaria, Mohamad Shukri

    Published 2020
    “…For this study, the main purpose is to apply the Particle Swarm Optimization (PSO) algorithm for use in searching for the optimal tool routing path for in simulation of drilling process…”
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  15. 15
    Adaptive Switching Gravitational Search Algorithm: An Attempt To Improve Diversity Of Gravitational Search Algorithm Through Its Iteration Strategy

    Adaptive Switching Gravitational Search Algorithm: An Attempt To Improve Diversity Of Gravitational Search Algorithm Through Its Iteration Strategy by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Shahdan, Sudin

    Published 2017
    “…The proposed ASw-GSA is also compared to original GSA, particle swarm optimization (PSO), genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). …”
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  16. 16
    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control

    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control by Shamsudin, Shamsudin, Mohamaddan, Shahrol

    Published 2023
    “…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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  17. 17
    Adaptive route optimization for mobile robot navigation using evolutionary algorithm

    Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

    Published 2021
    “…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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  18. 18
    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control

    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control by Razali, Muhammad Razmi, Mohd Faudzi, Ahmad Athif, Shamsudin, Abu Ubaidah, Shahrol Mohamaddan, Shahrol Mohamaddan

    Published 2023
    “…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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  19. 19
    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control

    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control by Razali, Muhammad Razmi, Mohd Faudzi, Ahmad Athif, Shamsudin, Abu Ubaidah, Mohamaddan, Shahrol

    Published 2023
    “…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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  20. 20
    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control

    A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control by Razali, Muhammad Razmi, Mohd Faudzi, Ahmad Athif, Shamsudin, Abu Ubaidah, Mohamaddan, Shahrol

    Published 2023
    “…Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). …”
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