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  1. 1
    Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization

    Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Bayuaji, Luhur, Syafrullah, Muhammad, Riyanto, Indra

    Published 2019
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  2. 2
    Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization

    Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Muhammad, Syafrullah, Indra, Riyanto

    Published 2019
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  3. 3
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    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 data-driven model is developed based on the exoskeleton prototype built. 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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  4. 4
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    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 data-driven model is developed based on the exoskeleton prototype built. 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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  5. 5
    Particle Swarm Optimization for Bluetooth Scatternet Formation

    Particle Swarm Optimization for Bluetooth Scatternet Formation by Kamel , Nidal

    Published 2005
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  6. 6
    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm

    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

    Published 2022
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  7. 7
    Bio-inspired for Features Optimization and Malware Detection

    Bio-inspired for Features Optimization and Malware Detection by Razak, Mohd Faizal Ab, Anuar, Nor Badrul, Othman, Fazidah, Firdaus, Ahmad, Afifi, Firdaus, Salleh, Rosli

    Published 2018
    “…The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. …”
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  8. 8
    Bio-inspired for Features Optimization and Malware Detection

    Bio-inspired for Features Optimization and Malware Detection by Mohd Faizal, Ab Razak, Nor Badrul, Anuar, Fazidah, Othman, Ahmad, Firdaus, Firdaus, Afifi, Rosli, Salleh

    Published 2018
    “…The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. …”
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  9. 9
    Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation

    Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

    Published 2019
    “…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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  10. 10
    Genetic Algorithms And Particle Swarm Optimization For Interference Minimization In Mobile Network Channel Assignment Problem

    Genetic Algorithms And Particle Swarm Optimization For Interference Minimization In Mobile Network Channel Assignment Problem by Loh, Ser Lee, Keek, Joe Siang, Wong, Yan Chiew, Woo, Xiu Juan, Lee, Wei Wen

    Published 2021
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  11. 11
    Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization

    Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization by Mousavi, M., Yap, Hwa Jen, Musa, S.N., Tahriri, F., Md Dawal, Siti Zawiah

    Published 2017
    “…In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. …”
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  12. 12
    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application

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

    Published 2011
    “…The optimal simulation parameters can be used for the real application. …”
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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

    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
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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  15. 15
    PSAT : a pairwise test data generation tool based on simulated annealing algorithm

    PSAT : a pairwise test data generation tool based on simulated annealing algorithm by Goh, Ghee Hau

    Published 2015
    “…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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  16. 16
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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  17. 17
    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed

    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
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  18. 18
    Parameter-Less Simulated Kalman Filter

    Parameter-Less Simulated Kalman Filter by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Saifudin, Razali

    Published 2017
    “…Simulated Kalman Filter (SKF) algorithm is a new population-based metaheuristic optimization algorithm. …”
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  19. 19
    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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  20. 20
    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
    “…This paper presents the simulation result of the effect of three GA parameters which are maximum iterations, population size and mutation probability on the developed algorithm. � 2008 IEEE.…”
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