Search Results - (( simulation optimization method algorithm ) OR ( parameter identification method algorithm ))*

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  1. 1
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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  2. 2
    Hybrid intelligent methods for parameter identification and load frequency control in power system

    Hybrid intelligent methods for parameter identification and load frequency control in power system by Aqeel Sakhy, Jaber

    Published 2014
    “…For example, the classical methods for parameter identification (LSE and MLE), the classical methods for LFC (PI, PD and PID) and the intelligent methods (fuzzy logic, neural network, genetic algorithm, and PSO). …”
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  3. 3
    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

    Published 2018
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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  4. 4
    Simulated real-time controller for tuning algorithm using modified hill climbing approach

    Simulated real-time controller for tuning algorithm using modified hill climbing approach by Ahmed, Ahmed Abdulelah

    Published 2014
    “…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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  5. 5
    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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  6. 6
    Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah

    Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah by Abdullah, Mohd Ikhwan

    Published 2010
    “…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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  7. 7
    Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems

    Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems by Mohd Helmi, Suid

    Published 2024
    “…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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  8. 8
    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines

    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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  9. 9
    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model

    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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  10. 10
    Modeling the powder compaction process using the finite element method and inverse optimization

    Modeling the powder compaction process using the finite element method and inverse optimization by Hrairi, Meftah, Chtourou, Hedi, Gakwaya, Augustin, Guillot, Michel

    Published 2011
    “…Thus, an integrated simulation module consisting of an inverse optimization method and a finite element method was developed for modeling the powder compaction process as a whole. …”
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  11. 11
    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

    Published 2015
    “…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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  12. 12
    System identification and pid control of toothbrush simulator system

    System identification and pid control of toothbrush simulator system by Mohd Yusoff, Ainul Husna

    Published 2019
    “…The PID controller was tuned through the PID tuner and Ziegler-Nichols method. Simulated and real-time system response from both tuning methods was compared. …”
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  13. 13
    Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model

    Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model by Azrag, Mohammed Adam Kunna, Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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  14. 14
    Discrete-time system identification using genetic algorithm with single parent-based mating technique

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. The study simulated single-input-single-output (SISO) models: ARX and NARX. …”
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  15. 15
    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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  16. 16
    Fuzzy modelling and control for a nonlinear reboiler system of a distillation column

    Fuzzy modelling and control for a nonlinear reboiler system of a distillation column by Ibrahim, Mohd. Faisal

    Published 2006
    “…Model parameters are tuned using Genetic algorithm (GA) and Recursive least square (RLS). …”
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  17. 17
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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  18. 18
    Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data

    Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data by Fitiwi, D. Z., K., S. Rama Rao.

    Published 2009
    “…Consequently, improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural network associated with three different training algorithms. …”
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  19. 19
    Optimization of process parameters for pyrolsis of waste plastics by T method-1

    Optimization of process parameters for pyrolsis of waste plastics by T method-1 by Shankaran A/l Thiyagarajan

    Published 2023
    text::Final Year Project
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  20. 20
    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi

    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi by Seyed Hossein, Mahdavi

    Published 2016
    “…Accordingly, in the second part of this research, the procedure of structural identification and damage detection has been developed by employing the wavelet-based method through the modified genetic algorithms (GAs) to optimally solve inverse problems. …”
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