Search Results - (( developing measures clustering algorithm ) OR ( java implication based algorithm ))
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data
“…This study aims to develop and demonstrate the effectiveness of the proposed clustering-based procedure with various similarity distance measures in detecting outliers. …”
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Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
Published 2010“…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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Unsupervised segmentation technique for acute leukemia cells using clustering algorithms
Published 2015“…Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively.Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…According to the literature, crowding distance as one of the most efficient algorithms was developed based on density measures to treat the problem of selection mechanism for archive update. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…The performance of the proposed algorithm is compared with a number of algorithms that are most commonly used and reported in the corresponding scientific literature such as K-means clustering, the C-link clustering and genetic algorithm using a well-known performance measure that combined cell load variations and a number of exceptional elements. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…According to the literature, crowding distance is one of the most efficient algorithms that was developed based on density measures to treat the problem of selection mechanism for archive updates. …”
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Abnormalities detection in apert syndrome using hierarchical clustering algorithms
Published 2025“…There are 12 skull angles and these angles are analysed using hierarchical clustering algorithms for identifying the outliers or abnormalities. …”
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A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study
Published 2022“…Gower distance was used for measuring similarity for mixed data types. To evaluate the clusters found; cluster distribution and Silhouette index were used for cluster quality, Cohen's Kappa Index for cluster stability and Cramer's V Coefficient for clinical relevance of clusters. …”
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BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. …”
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Density based subspace clustering: a case study on perception of the required skill
Published 2014“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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