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Showing 241 - 260 results of 716 for search '(((( data using algorithms ) OR ( data processing algorithm ))) OR ( elements mapping algorithm ))', query time: 0.13s Refine Results
  1. 241

    Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

    Published 1994
    “…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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    article
  2. 242

    Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

    Published 2023
    “…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”
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    A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

    Published 2021
    “…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
  6. 246

    Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

    Published 2022
    “…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”
  7. 247

    Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

    Published 2022
    “…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
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    masterThesis
  8. 248

    Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

    Published 2023
    “…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
  9. 249

    Three-phase simulated annealing algorithms for exam scheduling by Mansour, Nashat

    Published 2003
    “…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
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    conferenceObject
  10. 250

    A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS by Zerguine, Azzedine

    Published 2020
    “…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …”
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    article
  11. 251

    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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  12. 252

    Convergence behavior of the normalized least mean fourth algorithm by Zerguine, A.

    Published 2000
    “…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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    article
  13. 253

    Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

    Published 2025
    “…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”
  14. 254

    Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

    Published 2011
    “…We evaluate our algorithm on proteins taken from a Protein Data Bank. …”
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    conferenceObject
  15. 255

    A comparison of optimization heuristics for the data mapping problem by Mansour, Nashat

    Published 1997
    “…In this paper we compare the performance of six heuristics with suboptimal solutions for the data mapping problem of two dimensional meshes that are used for the numerical solution of Partial Differential Equations(PDEs) on multicomputers. …”
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    article
  16. 256

    Social spider optimization algorithm: survey and new applications by Abualigah, Laith

    Published 2024
    “…Finally, this chapter provides an expectation of the fields that need to work with this algorithm to improve problem-solving and the fields that have a growing number studies that use this algorithm.…”
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  17. 257

    IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture by Moutaz Alazab (17730060)

    Published 2025
    “…The IoMT manufacturers need to offer their products at a competitive price, which forces them to use simplified architecture, leaving limited and, to some extent, no scope to employ sophisticated cybersecurity algorithms. …”
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