Search Results - (( parameter estimation based algorithm ) OR ( parameters estimation methods algorithm ))*
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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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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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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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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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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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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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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…This paper compares different initialization methods and investigates their performance and effects on estimating kinetic parameters’ value in models of biological systems. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…Using GSA, the parameter estimation of the classifier and the peak feature selection can be done simultaneously. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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