Search Results - (( motion evaluation swarm algorithm ) OR ( a simulation based algorithm ))*

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  1. 1

    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…Two examples of meta-heuristics are Particle swarm optimization (PSO) and gravitational search algorithm (GSA), which are based on the social behavior of bird flocks and the Newton's law of gravity and the law of motion, respectively. …”
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  2. 2

    Liquid Slosh Control By Implementing Model-Free PID Controller With Derivative Filter Based On PSO by Mohd Tumari, Mohd Zaidi, Zainal Abidin, Amar Faiz, A Subki, A Shamsul Rahimi, Ab Aziz, Ab Wafi, Saealal, Muhammad Salihin, Ahmad, Mohd Ashraf

    Published 2020
    “…The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. …”
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  3. 3

    Liquid slosh control by implementing model-free PID controller with derivative filter based on PSO by Mohd Zaidi, Mohd Tumari, Amar Faiz, Zainal Abidin, A. Shamsul Rahimi, A. Subki, Ab Wafi, Ab Aziz, Muhammad Salihin, Saealal, Mohd Ashraf, Ahmad

    Published 2020
    “…The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. …”
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  4. 4

    Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

    Published 2018
    “…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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  5. 5

    A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

    Published 2014
    “…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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  6. 6
  7. 7

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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  8. 8

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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  9. 9

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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  10. 10

    Synchronous gravitational search algorithm vs asynchronous gravitational search algorithm: a statistical analysis by Abd Aziz, N.A., Ibrahim, Z., Nawawi, S.W., Sudin, S., Mubin, M., Abd Aziz, K.

    Published 2014
    “…Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. …”
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  11. 11

    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
    “…After which pbest-guide binary particle swarm optimization (PBPSO) is used to evaluate the most informative features from the original feature set. …”
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  12. 12

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  13. 13

    3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control by Muhammad Firdaus, Masrom

    Published 2020
    “…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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  14. 14

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    “…Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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  15. 15

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…This research also provided some results in combining the rule-based simulation with optimization: first, a feasible schedule was computed and then fine-tuned with the rule-based simulation system, then tested with RMS which is the reactive part. …”
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  16. 16

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  17. 17

    Performance of Ad-Hoc on-Demand Distance Vector Discovery Algorithms Based On Packet Lifetime by Ahmad, Noor Azlan

    Published 2008
    “…From the extensive simulations based on the performance metrics, the two proposed algorithms have shown distinct improvement and subsequently enhancing the performance of AODV.…”
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  18. 18

    A fault syndromes simulator for random access memories by Wan Hasan, Wan Zuha, Abdul Halim, Izhal, Mohd Sidek, Roslina, Othman, Masuri

    Published 2008
    “…The simulator allows a user through a GUI to select a March based test algorithm depending on the desired fault coverage and diagnostic resolution. …”
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  19. 19

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…A modified version of the SKF algorithm, named Opposition-Based SKF (OBSKF), introduced by K. …”
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  20. 20

    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

    Published 2017
    “…GridSim simulator has become a very popular simulation tool and has been widely used by Grid researchers to test and evaluate the performance of their proposed scheduling algorithms. …”
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