Search Results - (( parameter estimation means algorithm ) OR ( probable distribution function algorithm ))*

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  1. 1

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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    Thesis
  2. 2

    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
    “…The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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    Article
  3. 3

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The first agent employed fuzzy parameters such as, current with its means and variances and the second agent is the probability of outage capacity for each state. …”
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    Thesis
  4. 4

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…To describe relative probability of different random variables, Probability Density Function (PDF) and the Cumulative Density Function (CDF) are capable to specify its own characterization of Gaussian distributions. …”
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    Book Chapter
  5. 5

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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    Conference or Workshop Item
  6. 6

    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
    Article
  7. 7

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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    Thesis
  8. 8

    A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. Solution vector of ACO is presented by implementing density and distribution function to search for a better solution and to specify a probability functions for every particle (ant). …”
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    Article
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    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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    Article
  12. 12

    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
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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    Thesis
  13. 13

    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

    Published 2015
    “…On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. …”
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    Thesis
  14. 14

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

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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    Thesis
  15. 15

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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    Thesis
  16. 16

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses
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    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…The probability function of the counts is often complicated thus a method using numerical Laplace transform inversion for computing the probabilities and the renewal function is proposed. …”
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    Thesis