Search Results - (( data reduction methods algorithm ) OR ( parameter simulation model algorithm ))

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  1. 1

    Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach by Gholizadeh, Somayyeh

    Published 2018
    “…The proposed algorithms are evaluated by considering different metrics, computation modellings, and measurements on the simulation. …”
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    Thesis
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    Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems by Mohd Helmi, Suid

    Published 2024
    “…Simulation results underscore the robustness and superiority of the NSCA and NSCA-SED algorithms in these contexts, showcasing improvements ranging from 13.97% to 97.17% for Model Order Reduction, 17.76% to 99.37% for Nonlinear System Identification, and 84.51% to 89.47% for Data-driven Control when compared to the standard SCA. …”
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    Thesis
  4. 4

    Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform by Abu Talib, Muhammad Ashraf

    Published 2014
    “…The outcomes at the end of this project are first two set of data is obtain from the synthetic model which are historical and simulated data. …”
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    Final Year Project
  5. 5

    Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

    Published 2016
    “…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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    Thesis
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    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

    Published 2019
    “…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). However, it has several drawbacks come from randomly searching constraints that cause lousy optimization. …”
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    Thesis
  8. 8

    Development of data-driven controller for slosh suppression in liquid cargo vehicles by Mohd Falfazli, Mat Jusof, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Suid, Mohd Helmi, Saari, Mohd Mawardi

    “…Therefore, it is necessary to develop a control method that does not depend on plant models, which is known as the data-driven control approach. …”
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    Research Report
  9. 9

    Prediction of Total Maximum Daily Loads (TMDLs) of pollutants in river by using artificial neural network (ANN) / Khairunnisa Khairudin, Mohamed Syazwan Osman and Syahrul Fithry Se... by Khairudin, Khairunnisa, Osman, Mohamed Syazwan, Senin, Syahrul Fithry

    Published 2020
    “…Such deterministic model requires extensive data of the underlying process compared to artificial neural network (ANN) that simulates data based on data-driven method. …”
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    Conference or Workshop Item
  10. 10

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil

    Published 2013
    “…We have exploited the rank deficient of H to reduce the number of parameters characterizing the channel matrix and model it with the lower number of parameters that actually require a description of H. …”
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    Thesis
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    PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate by Muhammad Farith Nazreen, Abu Samah, Muhamad Sukri, Hadi, Abdul Malek, Abdul Wahab, Nadzirah, Mohd Mokhtar, Intan Zaurah, Mat Darus

    Published 2022
    “…Then, the linear autoregressive with exogenous (ARX) model is selected as a model structure for model development using system identification method via bird mating optimizer (BMO) algorithm. …”
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    Conference or Workshop Item
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    New optimization technique to design the core of three-phase transformer by Alyozbaky, Omar Sh., Ab Kadir, Mohd Zainal Abidin, Izadi, Mahdi, Gomes, Chandima, Azis, Norhafiz, Mohd Isa, Maryam

    Published 2019
    “…In achieving this target, a 3D finite element method had been used to simulate the proposed transformer model. …”
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    Conference or Workshop Item
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    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
  17. 17

    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
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    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