Search Results - (( using interactive method algorithm ) OR ( parameter simulation model algorithm ))

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  1. 1

    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
  2. 2

    Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm by Mok, Ren Hao, Raja Mohd Taufika, Raja Ismail, Mohd Ashraf, Ahmad

    Published 2017
    “…For simplicity, a single row wind farm model with turbulence interaction between turbines is used to validate the proposed approach. …”
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    Conference or Workshop Item
  3. 3

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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    Thesis
  4. 4

    Finite Element Modeling Of Ballistic Penetration into Fabric Armor by Talebi, Hossein

    Published 2006
    “…Finite element models of fabric impact were made with initial conditions extracted from literature and simulations were performed. …”
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    Thesis
  5. 5

    Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah by Airul Sharizli, Abdullah

    Published 2017
    “…Hence, the success of CAWS system relies very much on whether the activation algorithm or model used is able to indicate a minimum safe distance precisely and timely. …”
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    Thesis
  6. 6

    A NEW APPROACH IN EMPIRICAL MODELLING OF CO2 CORROSION WITH THE PRESENCE OF HAc AND H2S by PANCA ASMARA, YULI PANCA ASMARA

    Published 2011
    “…In order to study CO2 corrosion of carbon steel involving interactive effects of several key parameters, a proven systematic statistical method that can represent the multitude interactive effects is needed. …”
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    Thesis
  7. 7

    Improved model for blood glucose control using Multi-Parametric Model Predictive Control (MP-MPC) / Nur Farhana Mohd Yusof by Mohd Yusof, Nur Farhana

    Published 2019
    “…This study was undertaken to improve medical treatment for type 1 diabetes and critically ill patients with stress-hyperglycaemia by ensuring all parameters involved in glucose-insulin interaction physically are included in the model's equations. …”
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    Thesis
  8. 8

    Model-free controller design based on simultaneous perturbation stochastic approximation by Mohd Ashraf, Ahmad

    Published 2015
    “…In order to evaluate the effectiveness of our proposed scheme, a wind farm model with dynamic characterization of wake interaction between turbines is used and then the proposed method is applied to the Horns Rev wind farm. …”
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    Thesis
  9. 9

    Model-free wind farm control based on random search by Mohd Ashraf, Ahmad, Hao, Mok Ren, Raja Mohd Taufika, Raja Ismail, Ahmad Nor Kasruddin, Nasir

    Published 2017
    “…The Horns Rev wind farm model with turbulence interaction between turbines is used to validate the proposed approach. …”
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    Conference or Workshop Item
  10. 10

    Evaluation method of rationality of urban landscape facility design based on neural network by Wang, Fanglong, Zhuang, Qianda, Sun, Xiaoni, Lin, Dengfeng

    Published 2025
    “…Specifically, our work encompasses the following key aspects: 1) Introducing the relevant theoretical knowledge and research progress in urban landscape facility design. 2) Elucidating the basic principles and structures of the backpropagation neural network (BPNN), along with the proposal of an improved genetic algorithm-back propagation neural network (GA-BP) to address the limitations of BPNN. 3) Conducting experiments to determine the optimal parameters for the GA-BP model once training is finished. …”
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    Article
  11. 11

    An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

    Published 2025
    “…The research establishes an accurate kinematic model using Denavit-Hartenberg parameters and develops an efficient simplified envelope collisiondetection method. …”
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    Thesis
  12. 12
  13. 13

    Second law considerations in fourier heat conduction of a lattice chain in relation to intermolecular potentials by Christopher, G.J.

    Published 2016
    “…If the method used here is considered a more ”realistic” or feasible model of the physical reality, then a re-evaluation of some aspects of the standard theoretical methodology is warranted since the standard model solution profile does not accord with the simulation temperature profile determined here for this related model. …”
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    Conference or Workshop Item
  14. 14

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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    Final Year Project
  15. 15

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

    Published 2007
    “…The application has widespread in many areas especially in system and control engineering. Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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    Thesis
  16. 16

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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    Article
  17. 17

    Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

    Published 2011
    “…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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    Thesis
  18. 18

    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
  19. 19

    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2013
    “…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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    Article
  20. 20

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

    Published 2017
    “…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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    Thesis