Search Results - (( using identification using algorithm ) OR ( using estimation method algorithm ))

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  1. 1

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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    Student Project
  2. 2

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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    Thesis
  3. 3

    Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model by Ahmad, Mohd Ashraf

    Published 2021
    “…This paper presents the identification of the ThermoElectric Cooler (TEC) plant using a hybrid method of Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based on continuous-time Hammerstein model. …”
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    Article
  4. 4

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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    Conference or Workshop Item
  5. 5

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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    Thesis
  6. 6

    Identification of continuous-time hammerstein system using sine cosine algorithm by E. F., Junis, J. J., Jui, Mohd Helmi, Suid, Mohd Ashraf, Ahmad

    Published 2019
    “…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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    Conference or Workshop Item
  7. 7

    Orthogonal least square algorithm and its application for modelling suspension system by Ahmad, Robiah, Jamaluddin, Hishamuddin

    Published 2001
    “…One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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    Article
  8. 8

    Identification of hammerstain model using stochastic perturbation simultaneous approximation by Nurriyah, Mohd Noor

    Published 2016
    “…The SPSA based method is then used to estimate the parameters in both the linear and non-linear parts based on the given input and output data with the present of delay in time. …”
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    Undergraduates Project Papers
  9. 9

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…System identification is a technique used to obtain a mathematical model of a system by performing analysis of input-output characteristic of the system. …”
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    Conference or Workshop Item
  10. 10

    Mixed Unscented Kalman Filter and differential evolution for parameter identification by Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol

    Published 2013
    “…The aim is to model the coupled tank system using mixed UKF and DE method to estimate the parameters of the tank. …”
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    Article
  11. 11

    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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    Thesis
  12. 12

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…Generation gap used was 0.5 has shorten the algorithm conver-gence time without affecting the model accuracy.…”
    Article
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    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 first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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    Article
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    A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

    Published 2021
    “…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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    Article
  18. 18

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…Generation gap used was 0.5 has shorten the algorithm convergence time without affecting the model accuracy.…”
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    Article
  19. 19

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…The RBF network is popular among scientist and engineer and used in a number of wide ranging signal and control applications which includes the area of system identification or estimation. …”
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    Thesis
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