Search Results - (( parametric estimation _ algorithm ) OR ( parameter optimization method algorithm ))
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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…One method of overcoming this d1ficulty is by incorporating the spline interpolation algorithm into the nonlinear preprocessing procedure. …”
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Proceeding Paper -
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Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani
Published 2019“…This research therefore proposes the employment of Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. …”
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Parameter estimation of stochastic differential equation
Published 2012“…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. …”
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Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method
Published 2008“…Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. …”
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Proceeding Paper -
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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Thesis -
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Optimal model order selection for transient error autoregressive moving average (TERA) MRI reconstruction method
Published 2008“…Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…A parametric model based on Hill Muscle Model (HMM) to estimate the knee joint moment is developed for both experiments protocols. …”
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Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves
Published 2024“…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”
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Traditional and higher order sliding mode control of MEMS optical switch
Published 2010“…Tuning the parameters of the controllers is carried out by using particle swarm optimization (PSO) method instead of conventional try and error. …”
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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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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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Thesis -
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A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data
Published 2014“…A parametric mixture model of three different distributions is proposed to analyse heterogeneous survival data.The maximum likelihood estimators of the postulated parametric mixture model are estimated by applying an Expectation Maximization Algorithm (EM) scheme.The simulations are performed by generating data, sampled from a population of three component parametric mixture of three different distributions. …”
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Conference or Workshop Item -
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data
Published 2013“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Parametric maximum likelihood estimation of cure fraction using interval-censored data
Published 2013“…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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