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Showing 1 - 20 results of 240 for search '(((( data settings algorithm ) OR ( smart learning algorithms ))) OR ( elements method algorithm ))', query time: 0.12s Refine Results
  1. 1
    Mapping realistic data sets on parallel computers

    Mapping realistic data sets on parallel computers by Mansour, N.

    Published 1993
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  2. 2
    On the Optimization of Band Gaps in Periodic Waveguides

    On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

    Published 2025
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  3. 3
    Automatic keyword extraction from a real estate classifieds data set

    Automatic keyword extraction from a real estate classifieds data set by Devassy, Dibin

    Published 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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  4. 4
    Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem

    Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

    Published 2025
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  5. 5
    Data reductions and combinatorial bounds for improved approximation algorithms

    Data reductions and combinatorial bounds for improved approximation algorithms by Abu-Khzam, Faisal N.

    Published 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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  6. 6
    Allocating data to distributed-memory multiprocessors by genetic algorithms

    Allocating data to distributed-memory multiprocessors by genetic algorithms by Mansour, Nashat

    Published 2016
    “…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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  7. 7
    A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems

    A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems by Devinder Kaur (264278)

    Published 2023
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  8. 8
    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition

    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

    Published 2021
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  9. 9
    Variable Selection in Data Analysis: A Synthetic Data Toolkit

    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 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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  10. 10
    Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing

    Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing by Al Sadawi, Alia

    Published 2016
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  11. 11
    Physical optimization algorithms for mapping data to distributed-memory multiprocessors

    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 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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  12. 12
    Machine Learning-Based Approach for EV Charging Behavior

    Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

    Published 2021
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  13. 13
    Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning

    Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

    Published 2023
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  14. 14
    Prediction of EV Charging Behavior Using Machine Learning

    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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  15. 15
    Hardening the ElGamal cryptosystem in the setting of the second group of units. (c2011)

    Hardening the ElGamal cryptosystem in the setting of the second group of units. (c2011) by Fanous, Suzan Mohamad

    Published 2011
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  16. 16
    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data

    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

    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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  17. 17
    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain

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

    Published 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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  18. 18
    A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System

    A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

    Published 2021
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  19. 19
    Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices

    Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

    Published 2016
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  20. 20
    Next-generation energy systems for sustainable smart cities: Roles of transfer learning

    Next-generation energy systems for sustainable smart cities: Roles of transfer learning by Yassine Himeur (14158821)

    Published 2022
    “…However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. …”
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