Search Results - (( mode selection using algorithm ) OR ( java application customization algorithm ))
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Fast mode decision algorithm
Published 2011“…Fast mode decision is the developed algorithm intended for selectively choosing the mode decision used by the encoder. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. …”
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. …”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…Those methods are combined with the first part of the Hilbert–Huang transformation, namely, the empirical mode decomposition (EMD) algorithm. The EMD algorithm is employed to decompose the nonstationary and nonlinear time series dataset into a finite set of orthogonal decomposition components, which includes a set of intrinsic mode function and residual components. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…For the overall performances which were based on the six data sets, the &-AMH algorithm recorded the highest mean accuracy scores of 0.93 as compared to the other algorithms: the ^-Population (0.91), the &-Modes-RVF (0.81), the New Fuzzy &-Modes (0.80), A:-Modes (0.76), &-Modes-HI (0.76), £-Modes- HII (0.75), Fuzzy £-Modes (0.74) and £-Modes-UAVM (0.70). …”
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Mode selection mechanism to enable effective device-to-device communication system over different environments
Published 2019“…The mode selection mechanism is proposed using multi-criteria for decision-making technique, the mode selection mechanism based on Simple Additive Weighting (SAW) algorithm is used to wisely connect and switch between the available modes. …”
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Mode selection mechanism to enable effective device-to-device communication system over different environments
Published 2019“…The mode selection mechanism is proposed using multi-criteria for decision-making technique, the mode selection mechanism based on Simple Additive Weighting (SAW) algorithm is used to wisely connect and switch between the available modes. …”
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Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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The Use of Transmission Line Modelling to Test the Effectiveness of I-kaz as Autonomous Selection of Intrinsic Mode Function
Published 2017“…This paper proposed the implementation of Integrated Kurtosis-based Algorithm for z-filter Technique (I-kaz) to kurtosis ratio (I-kaz-Kurtosis) for that allows automatic selection of intrinsic mode function (IMF) that's should be used. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad
Published 2018“…A metaheuristic algorithm in the UFLS scheme can be used to select the best load combination in real time. …”
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Design and analysis of super twisting sliding mode control for machine tools
Published 2016“…The performance of tuned super twisting sliding mode controller was compared with a traditional sliding mode controller using sigmoidlike function. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
Published 2018“…The current research presents the implementation of an integrated kurtosisbased algorithm for a z-filter technique (Ikaz) to kurtosis ratio (Ikaz-kurtosis), for this allows automatic selection of the IMF that should be used. …”
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