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General applicability of genetic and simulated annealing algorithms for data mapping
Published 1995Get full text
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conferenceObject -
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
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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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masterThesis -
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Trajectory Planning and Resource Allocation of Multiple UAVs for Data Delivery in Vehicular Networks
Published 2019“…This letter jointly investigates the trajectory and radio resource optimization for multiple unmanned aerial vehicles (UAVs) to fully deliver critical data in vehicular networks during disaster situations. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
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masterThesis -
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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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masterThesis -
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