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developing forest » developing 21st (Expand Search)
forest algorithm » firefly algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
developing forest » developing 21st (Expand Search)
forest algorithm » firefly algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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masterThesis -
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General applicability of genetic and simulated annealing algorithms for data mapping
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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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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…The most important question when using multimodal data is how to fuse them—a field of growing interest among researchers. …”
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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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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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masterThesis -
57
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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Clustering/partitioning algorithms and comparative analysis
Published 1989Get full text
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masterThesis -
59
Analyzing the Influence of Climate and Anthropogenic Development on Vegetation Cover in the Coastal Ecosystems of GCC
Published 2025“…We used Landsat satellite imagery and a Random Forest classification algorithm to map various land cover classes along the GCC coastline. …”
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