Search Results - (( evolution detection method algorithm ) OR ( variable estimation method algorithm ))
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A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach
Published 2012“…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. …”
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Fitness value based evolution algorithm approach for text steganalysis model
Published 2013“…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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Text steganalysis using evolution algorithm approach
Published 2012“…This study presents a new alternative of steganalysis method in order to detect hidden messages in text steganalysis called Evolution Detection Steganalysis System (EDSS) based on the evolution algorithm approach under Java Genetic Algorithms Package (JGAP). …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Non detection zone decreases to around zero and the proposed method has the ability to detect islanding up to 0.1% power mismatch. …”
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The proposed method inherits the robustness properties of the original RFCH estimators. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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Differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. …”
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Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state. …”
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Parameter estimation of a continuous-time plant – the least-absolute error with variable forgetting factor method
Published 2005“…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state.…”
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…The results signify that our proposed RNGVS.RFCH method able to correctly select the important variables in the final model. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…The significant variables determined by maximum likelihood method were then estimated using the BLR method. …”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization
Published 2013“…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
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Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control.
Published 2011“…This paper expands a Multi Input Multi Output (MIMO) fuzzy estimator variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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