Search Results - (( parameter simulation approach algorithm ) OR ( parameter estimation using algorithm ))
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1
Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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2
Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso
Published 2023“…The ability to create “structured models” of biological simulations is becoming more and more commonplace. Although computer simulations can be used to estimate the model, they are restricted by the lack of experimentally available parameter values, which must be approximated. …”
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3
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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4
Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.]
Published 2011“…The main feature of the model is the development of the Fuzzy State Space Algorithm (FSSA) for determination of input parameters that can be applied to any multivariable dynamic system. …”
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Research Reports -
5
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
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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7
Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter
Published 2018“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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10
ACCURATE INDOOR POSITION ESTIMATION TECHNIQUE USING FINGERPRINTING AND LATERATION-BASED APPROACH IN BLUETOOTH TECHNOLOGY
Published 2012“…The novel approach used in the proposed hybrid approach is the use of Euclidian distance formula for distance estimation instead of propagation model. …”
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11
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We propose a new and efficient approximation of the concentration parameter estimates using two approaches, namely, the roots of a polynomial function and minimizing the negative value of the loglikelihood function in this study. …”
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12
A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…It is a further enhancement of a single-objective Simulated Kalman Filter (SKF) optimization algorithm. …”
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13
The Effect of Reparameterisation on the Behaviour of Nonlinear Estimates
Published 2000“…Reparameterization was used in order to remove or reduce the nonlinear behaviour of the parameter estimates. …”
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14
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Currently not much attention is given for using RLS for history matching purposes. Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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A Kalman Filter Approach for Solving Unimodal Optimization Problems
Published 2015“…This new algorithm is inspired by the estimation capability of the Kalman Filter. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
17
Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations
Published 2011“…These algorithms are used to approach, flyaround, and to depart form a target vehicle in elliptic orbits. …”
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18
Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations
Published 2014“…These algorithms are used to approach, flyaround, and to depart form a target vehicle in elliptic orbits. …”
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Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration
Published 2016“…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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20
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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