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  1. 1

    Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

    Published 2021
    “…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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  2. 2

    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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  3. 3

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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  4. 4

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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  5. 5

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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  6. 6

    Hybrid Improved Bacterial Swarm Optimization Algorithm for Hand-Based Multimodal Biometric Authentication System by Shanmugasundaram, Karthikeyan, Mohmed, Ahmad Sufril Azlan, Ruhaiyem, Nur Intan Raihana

    Published 2019
    “…This paper proposes a Hybrid Improved Bacterial Swarm (HIBS) optimization algorithm for the minimization of Equal Error Rate (EER) as a performance measure in a hand-based multimodal biometric authentication system. …”
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  7. 7

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    “…It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. …”
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  8. 8

    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy by Ehteram M., Banadkooki F.B., Fai C.M., Moslemzadeh M., Sapitang M., Ahmed A.N., Irwan D., El-Shafie A.

    Published 2023
    “…Decision making; Natural language processing systems; Bat algorithms; Heading policy; Multi-reservoir operation; Multi-reservoir systems; Optimization algorithms; Power- generations; Salp swarms; Seagull optimization algorithm; Swarm algorithms; Two-point; Optimization…”
    Article
  9. 9

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  10. 10

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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  11. 11

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…These two algorithms are compared to their original artificial intelligence algorithms, i.e. particle swarm optimization algorithm and genetic algorithm. …”
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  12. 12

    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem by Ismail, Ibrahim, Hamzah, Ahmad, Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Kamal, Khalil, Muhammad Arif, Abdul Rahim

    Published 2014
    “…The binary-based algorithms including the binary particle swarm optimization (BPSO) algorithm are proposed to solve discrete optimization problems. …”
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  13. 13

    A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

    Published 2023
    “…Dams; Irrigation; Particle swarm optimization (PSO); Bat algorithms; Global optimal solutions; Hybrid optimization algorithm; Multi-reservoir systems; Optimization algorithms; Optimization modeling; Particle swarm optimization algorithm; Reservoir operation; Reservoirs (water)…”
    Article
  14. 14

    Improving robot Darwinian particle swarm optimization using quantum-behaved swarm theory for robot exploration and communication / Duaa Mehiar by Duaa , Mehiar

    Published 2021
    “…In this study, a new algorithm called the Quantum Robot Darwinian Particle Swarm Optimization (QRDPSO) is contributed with the hypothesis that quantum behaving particles can address the RDPSO main gaps; i.e. to improve the exploration and communication performance of a swarm robotic system. …”
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  15. 15

    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

    Published 2023
    “…The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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  16. 16

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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  17. 17

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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  18. 18

    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. by Ambursa, Faruku Umar, Latip, Rohaya

    Published 2013
    “…Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Several researches have been conducted to tackle the problems of task scheduling for the heterogeneous and dynamic grid systems using different bio-inspired mechanisms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO). …”
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  19. 19

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    Published 2018
    “…Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researchers. …”
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  20. 20

    Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm by Chong K.L., Lai S.H., Ahmed A.N., Wan Jaafar W.Z., El-Shafie A.

    Published 2023
    “…Ant colony optimization; Hydroelectric power; Hydroelectric power plants; Investments; Particle swarm optimization (PSO); Reservoirs (water); Stream flow; Water supply; Ant colony algorithms; Hydro-power generation; Hydropower reservoirs; Optimization algorithms; Particle swarm optimization algorithm; Reservoir performance; Streamflow generations; Uncertainty and variability; Genetic algorithms…”
    Article