Search Results - (( initial solution based algorithm ) OR ( parameter simulation model algorithm ))

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  1. 1

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

    Published 2020
    “…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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    Final Year Project
  2. 2

    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 proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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    Article
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    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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    Thesis
  5. 5

    Modelling of Adsorption of Dyes from Aqueous Solution by Activated Carbon by Wong, Teck Ngin

    Published 2004
    “…Three set of experimental data from Choy et al. (2001) based on different masses were selected to test the applicability of the FPCDSD model in simulating batch adsorption. Simulation results show that, for acid dye/activated carbon system a single set of mass transfer parameters is able to match the simulation and experimental data using the FPCDSD model and the FCDSD model. …”
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    Thesis
  6. 6

    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

    Published 2010
    “…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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    Thesis
  7. 7

    Multi-parametric optimization of aerodynamic performance and pedestrian crash in sedan front-end profiles by Nor Azman, Afzatul Najwa

    Published 2025
    “…A multiobjective optimization framework was developed using computational simulations, mathematical modelling, and evolutionary algorithms. …”
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    Thesis
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    Mechanical and grain growth behaviour of wire-arc additive manufacturing (WAAM) of SS316L using experiment and numerical simulation / Muhd Faiz Mat @ Muhammad by Mat @ Muhammad, Muhd Faiz

    Published 2022
    “…As modelling a complex multi-pass welding simulation is a challenge due to the longer computational time, an innovative solution to simplify the Heat Source Model (HSM) was explored. …”
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    Thesis
  10. 10

    Design optimization of a hybrid electric vehicle powertrain by Mangun, Firdause, Mahmoud Idres, Moumen Mohammed, Abdullah, Kassim Abdulrahman,

    Published 2017
    “…Vehicle modelling is based on Quasi-Static-Simulation (QSS) backward-facing approach. …”
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    Proceeding Paper
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    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2017
    “…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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    Conference or Workshop Item
  13. 13

    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
  14. 14

    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
  15. 15

    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
  16. 16

    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
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    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
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    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
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    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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    Conference or Workshop Item
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