Search Results - (( using function method algorithm ) OR ( based simulation model algorithm ))

Refine Results
  1. 1

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…Conventionally, the numerical simulations for such devices are obtained by using the commercial simulation packages based on the Finite Element Methods (FEM). …”
    Get full text
    Get full text
    Thesis
  4. 4

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…The proposed method was validated using two-dimensional benchmark problems and the results were compared with results using the OC method. …”
    Get full text
    Get full text
    Article
  6. 6

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
    Get full text
    Get full text
    Thesis
  7. 7

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

    Published 2016
    “…Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  8. 8

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…In recent works, it was shown that the SEF can be approximated using tangential hyperbolic function (THF) for Hammerstein and Wiener NLFXLMS algorithms, such that the degree of nonlinearity can be estimated using modelling approach. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

    Published 2020
    “…The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

    Published 2012
    “…Simulation results show that the performance of the THF-based NLFXLMS algorithm is comparable with the SEF-based NLFXLMS.…”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
    Get full text
    Article
  15. 15

    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

    Published 2006
    “…Two metamodeling techniques namely the neural network and the response surface methodology are used and compared to approximate two multidimensional functions. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model by Yazid, Edwar, Liew, M. S., Parman, Setyamartana, Kurian, V.J.

    Published 2013
    “…Here, we outline a practical algorithm for TVARX model which uses expectation-maximization (EM) algorithm based on Kalman smoother to generate the transfer function. …”
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    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
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
  18. 18

    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
    “…First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The issue of model parsimony is also addressed, and the model is validated using correlation tests. …”
    Get full text
    Get full text
    Article