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  1. 1

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

    Published 2003
    “…One method of overcoming this d1ficulty is by incorporating the spline interpolation algorithm into the nonlinear preprocessing procedure. …”
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    Proceeding Paper
  2. 2

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The second controller design strategy is based on a cost function optimization using GAS. …”
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    Thesis
  3. 3

    Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm by Salami, Momoh Jimoh Emiyoka, Najeeb, Athaur Rahman

    Published 2012
    “…The use of parametric modelling approach for Magnetic Resonance Imaging (MRI) reconstruction has been shown to produce images with higher resolution compared to the use of Fast Fourier Transform (FFT) technique. …”
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    Monograph
  4. 4

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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    Thesis
  5. 5

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

    Published 2024
    “…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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    Article
  6. 6

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

    Published 2012
    “…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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    Article
  7. 7

    Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method by Aibinu, Abiodun Musa, Najeeb, Athaur Rahman, Salami, Momoh Jimoh Emiyoka, Shafie, Amir Akramin

    Published 2008
    “…An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. …”
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    Proceeding Paper
  8. 8

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. …”
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    Article
  9. 9

    Optimal model order selection for transient error autoregressive moving average (TERA) MRI reconstruction method by Najeeb, Athaur Rahman, Salami, Momoh Jimoh Eyiomika, Aibinu, Abiodun Musa, Shafie, Amir Akramin

    Published 2008
    “…An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. …”
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    Article
  10. 10

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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    Thesis
  11. 11

    Development of Fluid Properties Correlation For Malaysian Crude by Ramli, Nazrin

    Published 2013
    “…GMDH is a family of inductive algorithms for computer-based mathematical modeling of multi-parametric datasets that features fully automatic structural and parametric optimization of models. …”
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    Final Year Project
  12. 12

    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

    Published 2016
    “…A parametric model based on Hill Muscle Model (HMM) to estimate the knee joint moment is developed for both experiments protocols. …”
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    Thesis
  13. 13

    Semiparametric estimation with profile algorithm for longitudinal binary data by Suliadi, Suliadi, Ibrahim, Noor Akma, Daud, Isa

    Published 2013
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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    Article
  14. 14

    Traditional and higher order sliding mode control of MEMS optical switch by Keramati, Ehsan

    Published 2010
    “…Tuning the parameters of the controllers is carried out by using particle swarm optimization (PSO) method instead of conventional try and error. …”
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    Thesis
  15. 15

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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    Thesis
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    Parametric maximum likelihood estimation of cure fraction using interval-censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Al-Omari, Mohamad

    Published 2013
    “…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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    Article
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