Search Results - (( parameter estimation case algorithm ) OR ( using function a algorithm ))

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  1. 1

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…This enhancement produces the filtering solution by using the second sub-algorithm. In addition, an improvement is made in the third sub-algorithm where the minimum output residual is combined with the cost function. …”
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    Thesis
  2. 2

    A new robust computational approach for the electric power system parameters by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F., Krebs, K.L.

    Published 2017
    “…The state estimation (SE) is a fundamental data processing algorithm used by the control centers of modern power networks. …”
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    Article
  3. 3

    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions by Yaakob, Mohd. Shafiek

    Published 2004
    “…It was found that, in most cases, the CFS performs better than the SFS with similar number of adjustable parameters. …”
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  4. 4

    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz

    Published 2015
    “…In this paper, an approach termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is basically based on Gravitational Search Algorithm (GSA), is proposed to combine these two parts into a simultaneous solution. …”
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    Article
  5. 5
  6. 6

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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    Article
  7. 7

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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  8. 8

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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  9. 9

    On a new transmuted three-parameter lindley distribution and its applications by Xi, Yuhang, Lu, Hezhi, Liang, Fei

    Published 2024
    “…In this paper, a new transmuted three-parameter Lindley distribution (TTHPLD) is established using the transmutation map method, which includes the Lindley distribution, two-parameter Lindley distribution, transmuted two-parameter Lindley distribution and three-parameter Lindley distribution as special cases. …”
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    Article
  10. 10

    Variable Speed Control Of Two-Mass Wind Turbine System Via State Feedback With Adaptation Law by Mohamad Murad, Nor Syaza Farhana

    Published 2018
    “…Wind turbine convert kinetic energy from the wind to rotational energy and then to electrical energy.In a wind energy conversion system (WECS),its electrical power control (EPC) side demanded a maximum mechanical power from the mechanical power control (MPC) side despite any intermittent wind and seasonal interference.Therefore,it is necessary to develop a variable speed algorithm for a modern WECS.For a two-mass horizontal axis wind turbine, the rotor and generator stiffness is commonly being neglected in the system dynamic.The inclusion of stiffness in system dynamic introduces integral term in the system expression and hence,incur mathematical complexity in the controller design phase.Contrary,this study consider stiffness as unknown parameter in the wind turbine dynamic.In order to obtain the maximum output power,the design of an algorithm with adaptation law for the speed control of a two-mass wind turbine system with an unknown stiffness is proposed in this research.The algorithm is formulated using a full-state feedback.In pursuance of solving the tracking control as a regulation case,the speed of the turbine is bijective mapped into the error dynamic.The stability of the proposed algorithm is guaranteed by Lyapunov.The adaptation law used in the variable speed algorithm is to successfully acquire the adaptability of the algorithm towards an unknown stiffness.Therein,the estimated stiffness is augmented in the Lyapunov function.The Lie derivative of the function is made into a negative semi-definite via the non-negative control parameters.In order to control the rotor speed to sustain the optimum tip-speed ratio (TSR),as well as obtaining the maximum power output from the turbine,the proposed algorithm is constructed.A MATLAB with Simulink® toolbox is used to validate the effectiveness of the proposed control speed.The simulation result showed that the rotor speed achieved an asymptotic tracking towards the demanded rotor speed irrespective of the stiffness value.The error is proved to be minimized as the integral of absolute error (IAE) obtained for wind turbine with stiffness ranging from 134550 Nmrad-1,269100 Nmrad-1,and 403650 Nmrad-1 are recorded as 0.003088,0.003063 and 0.003088 respectively. …”
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  11. 11

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…This research investigated the non-parametric maximum likelihood estimation method for cure rate estimation by considering two common estimators for the survival function: 1) The Kaplan Meier (KM) estimator, which is suitable for the right censoring case; and 2) The Turnbull Estimator, which is suitable for the interval type of data censoring. …”
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  12. 12

    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
    “…In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. …”
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    Article
  13. 13

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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  14. 14

    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

    Published 2019
    “…On the one side, the estimation Transfer Function (TF) of these motors is considered a significant problem in most previous studies which causes bad controller design, if the low estimation accuracy. …”
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  15. 15

    Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

    Published 2010
    “…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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  16. 16

    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
    “…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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  17. 17

    Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner by Giman, Maureen, Muhamad Zuraidi, Siti Zulaikha, Moner, Syahida Asyikin

    Published 2022
    “…Meanwhile, the Levenberg-Marquadt method uses the gradient descent algorithm, which also has a similar algorithm to the Gauss-Newton method in finding the value for the unknown parameter.…”
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    Student Project
  18. 18

    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
    “…It also has the strength of adapting unimodal functions with bathtub shape. Estimating the parameter of EWD distribution poses another problem as the flexibility calls for the introduction of an additional parameter. …”
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  19. 19

    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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  20. 20

    A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

    Published 2015
    “…The model is simple in application with the use of genetic algorithm for model calibration making use of only the material fatigue limit. …”
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