Search Results - (( parameter detection method algorithm ) OR ( parameters iteration method algorithm ))
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…The proposed estimation approach simplifies the typical trial-and-error method. During optimization, within 100 iterations, the chewing count is reduced by 12.9% from its first iteration. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…The proposed estimation approach simplifies the typical trial-and-error method. During optimization, within 100 iterations, the chewing count is reduced by 12.9% from its first iteration. …”
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Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…The Expectation Maximization (EM) was considered to obtain the estimate of the parameters. These estimates were then compared to the Newton-Raphson iteration method. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique
Published 2023Conference Paper -
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Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…Therefore, two automated procedures are developed to determine these parameters iteratively. The FBTS integrated with automated edge-preserving regularization algorithm is implemented in C++ programming language executed in parallel computing. …”
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7
CT reconstruction algorithm and low contrast detectability of phantom study: a systematic review and meta-analysis
Published 2022“…Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. …”
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Impact of low-dose protocols on computed tomography of lung cancer screening on the intrinsic performance metrics: a phantom study
Published 2023“…Introduction: This research aims to assess the task-based performance of low dose CT lung examination with different acquisition parameters, evaluate the acquisition parameters of lung cancer in low dose CT lung examination, and explore the effect of the iterative reconstruction (IR) algorithm on the image quality of low dose CT for CT lung examination. …”
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Single Frame Profilometry With Rapid Phase Demodulation On Colour-Coded Fringes
Published 2019“…The findings prove that the proposed concept is applicable and provides an alternative method for conventional fringe analysis techniques such as transform-based algorithms or phase-shifting algorithms to advance high-speed 3D profilometry.…”
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11
Optimization of feature selection in Support Vector Machines (SVM) using recursive feature elimination (RFE) and particle swarm optimization (PSO) for heart disease detection
Published 2024“…RFE combines a dimensionality reduction process with a machine learning process where the least important features are iteratively removed until the best feature subset is obtained, while the PSO method is used to optimize the C and gamma parameters of SVM. …”
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Proceeding Paper -
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Mathematical modeling of brain tumor cell growth for passive, active and oxygen transport mechanism with microgravity condition / Norfarizan Mohd Said
Published 2018“…The sequential algorithms for these methods are developed and written in Matlab R2009a code to produce the numerical simulations of the models. …”
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13
Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML)
Published 2024“…During the first iteration, data were gathered using sensors that measured four parameters: pH, turbidity, temperature, and total dissolved solids (TDS). …”
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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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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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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…Two novel hierarchical structures are presented which extend the applicability of previous model based double iterative loop techniques to non-convex problems. The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real process optimality inspite of model reality differences. …”
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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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