Search Results - (( parameter selection means algorithm ) OR ( parameter estimation method algorithm ))

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  1. 1

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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    Conference or Workshop Item
  2. 2

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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    Thesis
  3. 3

    Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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    Article
  4. 4

    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
    “…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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    Article
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    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
    “…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
    Article
  7. 7

    Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

    Published 2012
    “…This verified the viability of the two-step method in the estimation of the drift and diffusion parameters of SDE with an improvement of a single knot selection.…”
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    Article
  8. 8

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Subsequent modification then involves substitution of an exponential function to the existing tangent hyperbolic function within formula p of the standard SMA in enabling improved probability variants via the selection of updated equations. Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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    Article
  9. 9

    Sensitivity analysis and optimization of a cardiovascular lumped parameter model for patient-specific modelling by Siti Munirah, Muhammad Ali, El-Bouri, Wahbi, Wan Naimah, Wan Ab Naim, Mohd Jamil, Mohamed Mokhtarudin

    Published 2025
    “…This study presents a framework that enhances parameter estimation in lumped parameter cardiovascular models by combining sensitivity analysis for parameter selection with multi-objective genetic algorithm optimization. …”
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    Article
  10. 10

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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    Thesis
  11. 11

    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model by MuhamadSafiih, L, Kamil, A.A., Abu Osman, M.T.

    Published 2014
    “…Through the bandwidth parameter also reveals that the estimated parameter is efficient, i.e., the S.D, MSE and RMSE values become smaller as N increased. …”
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    Article
  12. 12

    Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm by Kabiri, Keivan

    Published 2013
    “…Half numbers of these points were selected to determine the mentioned parameters using minimizing the sum of the squared residuals, and the other points were used for accuracy assessment of the applied method. …”
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    Thesis
  13. 13

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…Bayesian techniques for bivariate model have not yet received much attention due to the hitches in dealing with much more parameters. Literature on Bayesian extremes based on MCMC techniques are dealing with either Gibbs sampling method or MH method, or the combination of both methods. …”
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    Thesis
  14. 14

    Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

    Published 2013
    “…In this regard, genetic algorithm generates different initial conditions of premise parameters to and the best one. …”
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    Thesis
  15. 15

    Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal by Mohd Fadhlan, Mohd Yusof

    Published 2021
    “…Two empirical models for weld depth estimation were developed from the combination of these sound features and weld parameters using the multiple linear regression (MLR) and artificial neural network (ANN) methods. …”
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    Thesis
  16. 16

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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    Thesis
  17. 17

    Covariance matrix analysis in simultaneous localization and mapping by Nur Aqilah, Othman

    Published 2016
    “…Estimation at a specific time or also known as the filtering technique in estimation and control theory is a method to estimate the desired parameters from indirect and uncertain observations, taking into account the system and measurement errors. …”
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    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…The first method isbased on fuzzy genetic algorithm to overcome the premature convergence. …”
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    Thesis
  20. 20

    Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

    Published 2010
    “…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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    Thesis