Search Results - (( parameters estimation method algorithm ) OR ( data distribution using algorithm ))
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1
Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…Then, the data set values such as voltage, current and power factor are used to estimates the new values of RXB and RLC parameters. …”
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2
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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3
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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4
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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5
Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain
Published 2014“…First, voltage profile on source distribution system is estimated. The voltage profile is predicted using Independent Component Analysis (lCA) algorithm. …”
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6
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
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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7
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…The main contribution of the proposed method is the ability to estimate the parameters, given a small number of data which will usually be the case in practical applications. …”
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8
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…This study started with the analysis of extreme PM10 data based on maximum likelihood estimation technique. …”
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9
Dynamic robust bootstrap method based on LTS estimators
Published 2009“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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10
Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…Next we consider both the scale and shape parameters to be unknown under censored data. It is observed that the estimate of the shape parameter under the maximum likelihood method cannot be obtained in closed form, but can be solved by the application of numerical methods. …”
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11
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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13
Statistical approach on grading: mixture modeling
Published 2006“…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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14
Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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15
An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.
Published 2011“…Maximum likelihood estimation (MLE) method is proposed to estimate the parameters within the framework of expectation-maximization (EM) algorithm, Newton Raphson method also employed. …”
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16
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
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17
Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates
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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18
Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises
Published 2020“…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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19
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…Parameter estimation with maximum likelihood estimation is considered with applications of the count distributions to under dispersed and over dispersed count data from the literature.…”
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20
Development Of An Automatic Calculation Method For Ct Dose Estimation Based On Individual Specific Size In Paediatric Population
Published 2022“…This study also aims to develop an automatic calculator using MATLAB algorithm for accurate patient size measurement and SSDE calculation. …”
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