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  1. 1
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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
    “…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  2. 2
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…System Identification, a discipline for constructing models from dynamic systems, consist of three major steps: structure selection, parameter estimation and model validation. …”
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  3. 3
    Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso

    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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  4. 4
    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. …”
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  5. 5
    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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  6. 6
    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2014
    “…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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  7. 7
    Power System State Estimation In Large-Scale Networks

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The quality of estimated results will depend on the measurements, the assumed network model and its parameters. …”
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  8. 8
    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)

    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO) by Jasni, Mohamad Zain, Azrag, Mohammed Adam Kunna, Saiful Farik, Mat Yatin, Aldehim, Ghadah, Zuhaira, Muhammad Zain, Shaiba, Hadil, Alturki, Nazik, Sapiah, Sakri, Azlinah, Mohamed, Jaber, Aqeel S.

    Published 2024
    “…Thus, obtaining accurate kinetic data for all reactions in an E. coli metabolic model is a technically-challenging process. So, Garra Rufa-inspired Optimization (GRO) Algorithm is applied to the primary metabolic network of E. coli as a model to estimate small-scale kinetic parameters and increase the kinetic accuracy. …”
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  9. 9
    Large-scale kinetic parameters estimation of metabolic model of escherichia coli

    Large-scale kinetic parameters estimation of metabolic model of escherichia coli by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Kabir, M. Nomani, Jaber, Aqeel S.

    Published 2019
    “…In this work, the PSO algorithm has been adopted to estimate the kinetic parameters by minimizing the errors of the large-scale of metabolic model response of E. coli with reference to real experimental data. …”
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  10. 10
    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. …”
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  11. 11
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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  12. 12
    Genetic Algorithm Based Lightning Estimation Model

    Genetic Algorithm Based Lightning Estimation Model by Musse Mohamud, Ahmed, Mohammad Kamrul, Bin Hasan, Jong, F. Chen, Denis, Lee

    Published 2020
    “…Using the GA optimized parameter the estimations areprecise. To achieve estimation that is more accurate many trials are required to be carried out in order to determine the best fitness value. …”
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  13. 13
    Relative motion guidance, navigation and control for autonomous spacecraft rendezvous

    Relative motion guidance, navigation and control for autonomous spacecraft rendezvous by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…In this paper, the development of guidance, navigation, and control algorithms of an autonomous space rendezvous and docking system are presented. …”
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  14. 14
    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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  15. 15
    Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system

    Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system by Karimaldini, Fatemeh

    Published 2011
    “…The estimates of ANFIS models are compared with FAO-56 reduced-set PM ETO approaches and conventional empirical ETO equations (Hargreaves, priestly Tailor, Makkink, Blaney-Criddle and Turc) that are calibrated with the Genetic Algorithm technique. …”
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  16. 16
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    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
    “…Numerical simulations of non-Newtonian fluids are indispensable for optimization and monitoring of several industrial processes such as crude oil transportation, nuclear cooling, geothermal and fossil fuel production. The governing equations derived for non-Newtonian fluid models result in nonlinear differential equations. …”
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  17. 17
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…In addition, the structural parameters of a system can be accurately estimated through the proposed system identification methods for both cases of linear and nonlinear conditions. …”
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  18. 18
    Nonlinear partial differential equations model related to ethanol production

    Nonlinear partial differential equations model related to ethanol production by Ahmad Izul Fakhruddin, Azimi, Norazaliza, Mohd Jamil

    Published 2019
    “…The effect of the diffusion coefficient and the advection coefficient are investigated to simulate the dynamical behaviour of the system. Since the model is nonlinear partial differential equations (PDEs), Gear's algorithm, a numerical method was employed to solve the system while the Nelder-Mead method is utilised to estimate the value of the parameters. …”
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  19. 19
    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia

    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…The mathematical model is a system of ordinary differential equations (ODEs) with time-varying coefficients as opposed to the conventional model with constant coefficients. …”
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  20. 20
    Determination of tree stem volume : A case study of Cinnamomum

    Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

    Published 2013
    “…Relevant mathematical models are identified from the 684 models obtained in estimating the volume and the biomass equations used. …”
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