Search Results - (( parameter simulation model algorithm ) OR ( initial solution using 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
    “…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
  2. 2

    Kinetic Parameter Estimation in Alkylation of Benzene with 1-Decene through Hybrid Particle Swarm Optimization by Mohd Zulkefle, Nurul Farihah

    Published 2012
    “…Afterwards, the solution obtained using PSO algorithm is given as initial guesses to the Levenberg–Marquardt algorithm to determine the improved optimal solution. …”
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    Final Year Project
  3. 3
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    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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    Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain by Mohd Hussain, Mashitah

    Published 2014
    “…The voltage profile is predicted using Independent Component Analysis (lCA) algorithm. …”
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    Thesis
  7. 7

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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    Thesis
  8. 8

    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
  9. 9

    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
  10. 10

    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali by Jarinah , Mohd Ali

    Published 2017
    “…Therefore, a hybrid approach will be the best solution. In this research, a hybrid observer is designed using the combination of artificial intelligence (AI) algorithm and conventional observer. …”
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    Thesis
  11. 11

    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
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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
  14. 14

    Modeling of lead (II) ion adsorption on multiwall carbon nanotubes using artificial neural network and Monte Carlo technique by Al Jadir, Thaer, Alardhi, Saja Mohsen, Al-Sheikh, Farooq, Jaber, Alaa Abdulhady, Kadhim, Wafaa Abdul, Mohd Hasbi, Ab. Rahim

    Published 2023
    “…The effects of various parameters, including the solution pH, adsorbent dosage, initial concentration of Pb2+, and contact time, on the Pb2+ removal from wastewater were investigated experimentally. …”
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    Article
  15. 15

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

    Published 2017
    “…Seeking global optimum solution, GA was executed with different initial settings to obtain sets of optimal parameters. …”
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    Proceeding Paper
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    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
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    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
  19. 19

    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
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    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