Search Results - (( data estimation methods algorithm ) OR ( panel estimation _ algorithm ))
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Thesis -
2
Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions
Published 2022“…Based on the panel data of cities and towns in China, by using the generalized estimation method of a dynamic panel, through the construction of regional household consumption expenditure evaluation models, optimize the impact evaluation algorithm of household consumption expenditure in different regions, standardize critic indicators, and build the impact modeling of household consumption expenditure in combination with relevant algorithms such as the Engel coefficient. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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4
Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. Different PV tracking methods were also evaluated, taking into account the annual energy production. …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2013“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. Different PV tracking methods were also evaluated, taking into account the annual energy production. …”
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Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin
Published 2021“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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7
Spacecraft sun-pointing using coplanar solar panels data and magnetic field measurements
Published 2013“…The developed algorithm is applied to a spacecraft designed as a passively sun-pointed spacecraft with coplanar solar panels. …”
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Proceeding Paper -
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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10
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…It will help the researcher get the fitted graph model, correct data, and estimate the value based on the data’s behaviour. …”
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Semiparametric estimation with profile algorithm for longitudinal binary data
Published 2013“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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Attitude and deformation coupled estimation of flexible satellite using low-cost sensors
Published 2022“…The numerical results also demonstrate that including the flexibility model in the developed estimation equations enables the algorithm to successfully estimate the deformation at any solar panel location without the need for any conventional sensor that directly measures the strain and/or deformation.…”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The simulation study results and real data sets indicate that the proposed MRFCHCS+LAD-SCAD estimator was found to be the best method compared to other methods in this study.…”
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Thesis -
16
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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System identification using Extended Kalman Filter
Published 2017“…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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Student Project -
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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State estimation of the power system using robust estimator
Published 2016“…In the existence of gross errors, the proposed algorithm provides estimates as good as those that are achieved by the conventional method of the WLS when no gross error exists in the process data. …”
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