Search Results - (( model estimation methods algorithm ) OR ( panel estimation method 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 -
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Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm
Published 2023“…This project aims to measure the performances of various photovoltaic power plants in Malaysia based on local spectral irradiances using genetic algorithm. A Python computational model that uses genetic algorithms will be developed to estimate the optimal tilt angle and orientation angle as well as the solar power received for the solar sites. …”
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Final Year Project / Dissertation / Thesis -
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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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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023“…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. Linear, quadratic and linear-algorithmic regression models displayed almost identical results. …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2013“…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. Linear, quadratic and linear-algorithmic regression models displayed almost identical results. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE
Published 2014“…A controlled Cuk DC-DC converter was implemented and connected to a SunTech STP085B PV panel to verify the accuracy of the proposed method. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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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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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…The parameter estimation step is concerned with the estimation of model parameters once the structure is known. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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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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The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). …”
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Conference or Workshop Item -
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Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm
Published 2011Subjects: “…Gauss-Newton method…”
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Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…As we know, the Multinomial Probit Model (MPM) is a method which assumes that chosen observations are independent but according to researchers the MPM is rarely used due to computational difficulties in computing the maximum likelihood estimates (MLE) for estimate MPM parameters. …”
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