بدائل البحث:
using algorithm » cosine algorithm (توسيع البحث)
developing new » developing a (توسيع البحث), developing _ (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
new algorithm » deer algorithm (توسيع البحث), rd algorithm (توسيع البحث)
element » elements (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
developing new » developing a (توسيع البحث), developing _ (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
new algorithm » deer algorithm (توسيع البحث), rd algorithm (توسيع البحث)
element » elements (توسيع البحث)
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A comparison of data mapping algorithms for parallel iterative PDE solvers
منشور في 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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article -
45
An enhanced k-means clustering algorithm for pattern discovery in healthcare data
منشور في 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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article -
46
Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
منشور في 2021"…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …"
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article -
47
DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
منشور في 2022"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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احصل على النص الكامل
masterThesis -
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XBeGene: Scalable XML Documents Generator by Example Based on Real Data
منشور في 2012"…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …"
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conferenceObject -
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
منشور في 2000احصل على النص الكامل
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masterThesis -
55
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
منشور في 2023"…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …"
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article -
56
A Survey of Data Clustering Techniques
منشور في 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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احصل على النص الكامل
masterThesis -
57
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
منشور في 2020"…In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …"
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article -
58
A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
منشور في 2024"…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …"
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Bird’s Eye View feature selection for high-dimensional data
منشور في 2023"…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …"