Search Results - (( parameter estimation based algorithm ) OR ( parameter simulation approach algorithm ))

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  1. 1

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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    Thesis
  2. 2

    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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  3. 3

    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

    ACCURATE INDOOR POSITION ESTIMATION TECHNIQUE USING FINGERPRINTING AND LATERATION-BASED APPROACH IN BLUETOOTH TECHNOLOGY by SUBHAN, FAZLI

    Published 2012
    “…The prediction and filtering process is based on the selected signal parameter based on our experimental observations. …”
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    Thesis
  5. 5

    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
    “…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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  6. 6

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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    Thesis
  7. 7

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
    Article
  8. 8

    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
  9. 9

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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    Article
  10. 10

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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    Article
  11. 11

    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
    “…One of the most promising approaches is based on optimal inverse Xltering followed by fitting an autoregressive moving average ( A M ) model to the deconvolved data so that its AR parameters are determined by solving high order Yule- Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm. …”
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    Proceeding Paper
  12. 12

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…Numerical nonlinear simulations that illustrate the relative navigation, attitude estimation, guidance, and control algorithms performance and accuracy are evaluated in the current paper. …”
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    Proceeding Paper
  13. 13

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2014
    “…Numerical nonlinear simulations that illustrate the relative navigation, attitude estimation, guidance, and control algorithms performance and accuracy are evaluated in the current paper. …”
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    Article
  14. 14

    A Kalman Filter Approach for Solving Unimodal Optimization Problems by Zuwairie, Ibrahim, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Ibrahim, Shapiai, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2015
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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    Article
  15. 15
  16. 16

    Relative motion guidance, navigation and control for autonomous spacecraft rendezvous by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…These algorithms are used to approach, flyaround, and to depart form a target vehicle in elliptic orbits. …”
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    Proceeding Paper
  17. 17

    Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates. by I. Aljawadi, Bader Ahnad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Midi, Habshah

    Published 2011
    “…The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. The analysis provided the analytical solution and a simulation study for the cure rate parameter. …”
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    Article
  18. 18

    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration by Abdulbari, Hayder A., Fiona Ling, Wang Ming

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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    Conference or Workshop Item
  19. 19

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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    Thesis
  20. 20

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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    Monograph