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يعرض 1 - 20 نتائج من 181 نتيجة بحث عن '(( alignment network algorithm ) OR ((( data encoding algorithm ) OR ( data settings algorithm ))))', وقت الاستعلام: 0.13s تنقيح النتائج
  1. 1

    Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

    منشور في 2021
    الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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    The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

    منشور في 2023
    "…We focus on the combined influence of data encoding, qubit entanglement, and ansatz expressibility in hybrid quantum neural networks (HQNNs) for multi-class classification tasks. …"
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    Accurate multiple network alignment through context-sensitive random walk حسب Hyundoo Jeong (3840013)

    منشور في 2015
    "…Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. …"
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    Automatic keyword extraction from a real estate classifieds data set حسب Devassy, Dibin

    منشور في 2011
    "…Keywords are considered to be a solution to this problem and are now widely used to search the information over the internet.In this project we analyze a real estate classifieds data set, with an objective to find keywords that represent this data set. …"
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    Data reductions and combinatorial bounds for improved approximation algorithms حسب Abu-Khzam, Faisal N.

    منشور في 2016
    "…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …"
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    article
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

    منشور في 2024
    "…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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    article
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    Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

    منشور في 1992
    "…We also present a technique for efficient mapping of large data sets. The algorithms include a parallel genetic algorithm (PGA), a parallel neural network algorithm (PNN) and a parallel simulated annealing algorithm (PSA). …"
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    masterThesis
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    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

    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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    masterThesis
  15. 15

    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

    منشور في 2021
    "…This work investigates the problem of scheduling the processing of tasks with non-identical sizes and different priorities on a set of parallel processors. An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
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    article
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    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm حسب Saima Hassan (14918003)

    منشور في 2022
    "…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …"
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    A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) حسب Wehbe, Gioia Wahib

    منشور في 2016
    "…Additionally, it was able to identify several differentiable regions in the real data set and on different chromosomes. However, we noticed that chromosomes 1, 3 and 6 had the highest occurrence rate of differentiable motifs (9, 8 and 6 motifs respectively). …"
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    masterThesis
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    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval حسب Mohammed Tahar Habib Kaib (21633176)

    منشور في 2024
    "…The proposed algorithm has successfully maintained homogeneity to the original data set, reduced the execution time and occupied storage space, and led to decent monitoring performance.…"