Search Results - a distribution ((((methods algorithm) OR (means algorithm))) OR (based algorithm))
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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Differential equation fault location algorithm with harmonic effects in power system
Published 2023“…This study focuses on a single line-to-ground (SLG) fault location algorithm in a power system distribution network based on fundamental frequency measured using the differential equation method. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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Analysis Of Large In-Plane Displacement And Strain In Rubber Using 2-D Scanner-Based Digital Image Correlation
Published 2017“…A new algorithm for mapping large deformation in the uNR specimens in a single-step without the need for a series of deformation images has also been developed. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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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“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes
Published 2012“…The filter algorithm is based on an enhanced harmonic mean filter algorithm. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…Literature on Bayesian extremes based on MCMC techniques are dealing with either Gibbs sampling method or MH method, or the combination of both methods. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Data clustering is one of the most popular branches in machine learning and data analysis. Partitioning-based type of clustering algorithms, such as K-means, is prone to the problem of producing a set of clusters that is far from perfect due to its probabilistic nature. …”
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Enhanced Automated Framework For Cattle Tracking And Classification
Published 2022“…Computer vision-based methods could be used to monitor each individual cows. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…The AADS algorithm uses evolving methods which are evolving autonomous data partitioning (eADP) and non-weighted frequency equations. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm
Published 2017“…The aim of this study was to use the geographical information system (GIS) to visualize the dengue incidences on a weekly basis in Selangor, Malaysia. Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…The second part of the study is on the confidence intervals (CI) for the concentration parameter in von Mises distribution. Several methods in constructing the CI for the concentration parameter are proposed including CI based on circular population, CI based on the asymptotic distribution of ˆ , CI based on the distribution of 휃 and 푅 and also CI based on bootstrap-t method. …”
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A balanced partitioning mechanism for multicontroller placement in software-defined wide area networks
Published 2022“…Moreover, the BPM is designed based on a modified K-means algorithm. BPM comprises of two approaches: the initialization method and the partitioning strategy. …”
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