Search Results - (( a simulation optimization algorithm ) OR ( data estimation using algorithm ))

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  1. 1

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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    Article
  2. 2

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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    Student Project
  3. 3

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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    Research Reports
  4. 4

    BSKF: Binary Simulated Kalman Filter by Zulkifli, Md. Yusof, Ismail, Ibrahim, Siti Nurzulaikha, Satiman, Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz

    Published 2015
    “…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF).Every agent in SKF is regarded as a Kalman filter. …”
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    Conference or Workshop Item
  5. 5

    Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso by Mohammed Adam Kunna, Azrag, Jasni Mohamad, Zain, Tuty Asmawaty, Abdul Kadir, Marina, Yusoff, Jaber, Aqeel Sakhy, Abdlrhman, Hybat Salih Mohamed, Ahmed, Yasmeen Hafiz Zaki, Husain, Mohamed Saad Bala

    Published 2023
    “…In this study, an Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm that can estimate the values of small-scale kinetic parameters is described and applied to E. coli’s main metabolic network as a model system. …”
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    Article
  6. 6

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

    Published 2012
    “…Activation energies of elementary steps were estimated by using Hybrid Particle Swarm Optimization (HPSO) algorithm. …”
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    Final Year Project
  7. 7
  8. 8

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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    Article
  9. 9

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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    Thesis
  10. 10

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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    Conference or Workshop Item
  11. 11
  12. 12

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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    Article
  13. 13

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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    Thesis
  14. 14

    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
    “…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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    Proceeding Paper
  15. 15

    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
    “…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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    Article
  16. 16

    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…Hence, a joint pilot symbol and placement scheme is proposed that optimizes over both the pilot symbol values and their placements as a single design optimization problem. …”
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    Thesis
  17. 17

    Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

    Published 2014
    “…When the differences between the observed performance data and simulated data are found, the iterations are made to modify the accuracy of the match. …”
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    Final Year Project
  18. 18

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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    Thesis
  19. 19

    Accurate range free localization in multi-hop wireless sensor networks by Abdulwahhab, Abdullah Raed

    Published 2019
    “…Finally, the GMSDP- algorithm achieves and provides a better value of RMSEs and the greatest localization estimation errors comparing with the CRLR algorithm and WLS algorithm.…”
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    Thesis
  20. 20

    On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

    Published 2020
    “…From Fig.4.3, in chapter 4, the maximal value of data rates = (17.4, 16.9,16.3) bits/s/Hz, when the optimal transmit pilot reuse was = (14, 17, 20), with accounting channel estimation, when the number of antennas was . …”
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    Thesis