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  1. 1
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    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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  2. 2
    Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm

    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
    “…This paper presents a preliminary study of a model-free approach based on spiral dynamic algorithm (SDA) for maximizing wind farms power production. …”
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  3. 3
    Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah

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

    Published 2017
    “…To represent the adaptive minimum safe distance which will be used in activation algorithm for CAWS, the new distance-based CAWS model, namely Minimum Safe Distance Gap (MSDG) is introduced. …”
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  4. 4
    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy

    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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  5. 5
    Finite Element Modeling Of Ballistic Penetration into Fabric Armor

    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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  6. 6
    A NEW APPROACH IN EMPIRICAL MODELLING OF CO2 CORROSION WITH THE PRESENCE OF HAc AND H2S

    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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  7. 7
    Model-free controller design based on simultaneous perturbation stochastic approximation

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

    Published 2015
    “…Furthermore, the performance of the MR-SPSA-based method is also compared with other existing model-free methods, in terms of maximum power production and convergence time.…”
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  8. 8
    Model-free wind farm control based on random search

    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
    “…This paper explores a model-free approach based on the random search (RS) algorithm for maximizing wind farms power production. …”
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  9. 9
    Evaluation method of rationality of urban landscape facility design based on neural network

    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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  10. 10
    An enhanced motion planning method for industrial robots based on the digital twin concept

    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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  11. 11
    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway

    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

    Published 2023
    “…Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. …”
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  12. 12
    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE

    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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  13. 13
    Estimation in spot welding parameters using genetic algorithm

    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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  14. 14
    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter

    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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  15. 15
    Simulation algorithm of bayesian approach for choice-conjoint model

    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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  16. 16
    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

    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. …”
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  17. 17
    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data

    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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  18. 18
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    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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  19. 19
    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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  20. 20
    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab

    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

    Published 2025
    “…The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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