Search Results - optimal ((step algorithm) OR (((((based algorithm) OR (swarm algorithm))) OR (search algorithm))))

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  1. 1

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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    Thesis
  2. 2

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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  3. 3
  4. 4

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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    Thesis
  5. 5

    Task scheduling on computational grids using Gravitational Search Algorithm by Zarrabi, Amirreza, Samsudin, Khairulmizam

    Published 2014
    “…We evaluate this approach with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) method. …”
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    Article
  6. 6

    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system by Nasir, Ahmad Nor Kasruddin, Abdul Razak, Ahmad Azwan

    Published 2022
    “…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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  7. 7

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…Particle Swarm Optimization (PSO) is a population based stochastic optimization technique which consist of particles that move collectively in iterations to search for the most optimum solutions. …”
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    Thesis
  8. 8

    An Efficient Control Implementation for Inverter Based Harmony Search Algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

    Published 2017
    “…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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  9. 9

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  10. 10

    A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

    Published 2023
    “…Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control…”
    Article
  11. 11

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”
    thesis::doctoral thesis
  12. 12

    An efficient control implementation for inverter based harmony serach algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

    Published 2017
    “…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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    Article
  13. 13

    An efficient control implementation for inverter based harmony search algorithm by Najeeb M., Daniyal H., Razali R., Bin Mansor M.

    Published 2023
    “…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
    Article
  14. 14
  15. 15

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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    Thesis
  16. 16

    An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

    Published 2023
    “…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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  17. 17

    Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

    Published 2014
    “…The main intention of this study is to find the significant peak features in time domain approach and this can be done using feature selection methods such as gravitational search algorithm (GSA) and particle swarm optimization (PSO). …”
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    Conference or Workshop Item
  18. 18

    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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    Thesis
  19. 19

    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

    Published 2015
    “…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
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  20. 20

    Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

    Published 2020
    “…Besides that, another limitation that exists in previous researches is the absence of parameter optimization for the classifier. Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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