Search Results - (( data generation clustering algorithm ) OR ( parallel optimization means algorithm ))
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1
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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Thesis -
2
Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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3
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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4
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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5
MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters
Published 2012“…MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. …”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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7
Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters
Published 2011“…K-means clustering produce a number of separate flat (non-hierarchical) clusters and suitable for generating globular clusters. …”
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A study of density-grid based clustering algorithms on data streams
Published 2011“…Clustering data streams attracted many researchers since the aPlications that generate data streams have become more popular. …”
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CC_TRS: continuous clustering of trajectory stream data based on micro cluster life
Published 2017“…In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. …”
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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A genetic algorithm (GA) is also used to find the best centroids for all the clusters generated cluster centroids. …”
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11
Optimized clustering with modified K-means algorithm
Published 2021“…Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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Incremental interval type-2 fuzzy clustering of data streams using single pass method
Published 2020“…The proposed algorithm produces clusters by determining appropriate cluster centers on a certain percentage of available datasets and then the obtained cluster centroids are combined with new incoming data points to generate another set of cluster centers. …”
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…The clusters formed revealed the capability and drawbacks of each algorithm on the data points.…”
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A buffer-based online clustering for evolving data stream
Published 2019“…Recently, a fully online clustering algorithm for evolving data stream called CEDAS was proposed. …”
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Knowledge-based genetic algorithm for multidimensional data clustering
Published 2013“…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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Proceeding Paper -
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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17
MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…The offline phase generates the final clusters using an adapted density-based clustering algorithm. …”
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Autonomous and deterministic supervised fuzzy clustering
Published 2010“…The model is tested on medical diagnosis benchmark data and Westland vibration data. The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. …”
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Knowledge-based genetic algorithm for multidimensional data clustering
Published 2014“…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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