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A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020“…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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A Survey of Data Clustering Techniques
Published 2023“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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Clustering/partitioning algorithms and comparative analysis
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…New technologies, such as Next-Generation Genome Sequencing, can now provide huge amounts of data in little time. Big initiatives such as the International Hapmap Project and the 1000 Genome project are making use of these technologies to provide the scientific community with a detailed genetic reference from different populations. …”
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