Search Results - (( simulation optimization _ algorithm ) OR ( parameter optimization based algorithm ))*

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  1. 1
    Optimization of turning parameters using genetic algorithm method

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

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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  2. 2
    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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  3. 3
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    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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  4. 4
    An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system

    An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system by Badaruddin Muhammad, Dwi Pebrianti, Normaniha Abdul Ghani, Nor Hidayati Abdul Aziz, Nor Azlina Ab Aziz, Mohd Saberi Mohamad, Mohd Ibrahim Shapiai, Zuwairie Ibrahim

    Published 2018
    “…Compared to another well-established optimizer, such as particle swarm optimization (PSO), the SKF algorithm is a relatively new optimizer and most importantly, the SKF algorithm has not been applied to parameter tuning of PID controller. …”
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  5. 5
    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems

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

    Published 2022
    “…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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  6. 6
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  7. 7
    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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  8. 8
    A multiobjective simulated Kalman filter optimization algorithm

    A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

    Published 2018
    “…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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  9. 9
    DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING

    DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING by K. S. , Rama Rao, Azrul, Hisham Bin Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
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  10. 10
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  11. 11
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  12. 12
    Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays

    Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays by Prajindra�Sankar K., Kiong T.S., Siaw�Paw J.K.

    Published 2023
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  13. 13
    Design optimization of a bldc motor by genetic algorithm and simulated annealing

    Design optimization of a bldc motor by genetic algorithm and simulated annealing by K.S.R., Rao, A.H.B., Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
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  14. 14
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  15. 15
    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
    “…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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  16. 16
    BBO algorithm-based tuning of PID controller for speed control of synchronous machine

    BBO algorithm-based tuning of PID controller for speed control of synchronous machine by Kasilingam G., Pasupuleti J.

    Published 2023
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  17. 17
    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING

    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K., S. Rama Rao., C. , -K, Chew

    Published 2009
    “…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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  18. 18
    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING

    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K.S., Rama Rao, C. K., Chew

    Published 2009
    “…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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  19. 19
    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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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
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