Search Results - (( making based method algorithm ) OR ( parameter estimation method algorithm ))
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…That is why many parameter estimation methods have been developed since their first introduction to determine the best value for a particular parameter. …”
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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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Dynamic robust bootstrap method based on LTS estimators
Published 2009“…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model
Published 2021“…The efficiency of the proposed method is evaluated based on the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon’s rank test. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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Artificial intelligence techniques applied as estimator in chemical process systems - A literature survey
Published 2015“…However, the various types of AI methods available make it difficult to decide on the most suitable algorithm to be applied for any particular system. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…Due to the complexity of GMM, we use Expectation Maximization (or EM) algorithm by Dempster et al. (1977) to obtain the maximum likelihood estimates of the GMM parameters. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates
Published 2017“…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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Towards a unified image quality assessment technique for cross-content image processing applications
Published 2024“…It can reconstruct images with five distortion types, outperforming SOTA AS algorithms, even under high distortion. The first stage uses an application-specific reconstruction algorithm, while the second stage employs an IQA-based model called the observation-based bilateral filter (OBF) with non-linear weights calculated using a Haar-PSI-based maximum a posteriori (MAP) estimator. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…This thesis proposes a hybrid indoor positioning method for single base station systems by jointly utilizing the fingerprinting method and geometric multilateration. …”
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A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm
Published 2015“…The model is simple in application with the use of genetic algorithm for model calibration making use of only the material fatigue limit. …”
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Speed sensorless control for PMSM drives using Extended Kalman Filter
Published 2021“…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…A novel channel estimation method is presented in this thesis relying on the reduction of the rank order of the total channel matrix H. …”
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Validation on 3D surface roughness algorithm for measuring roughness of psoriasis lesion
Published 2010“…Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…Six NARX models which represent Normal and other five categories of heart diseases such as Atrial Septal Defect (ASD), Pulmonary Stenosis (PS), Patent Ductus Arteriosus (PDA), Ventricular Septal Defect (VSD) and Mitral Regurgitation (MR) are estimated. A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
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