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Showing 101 - 120 results of 526 for search '(( element method algorithm ) OR ((( data based algorithm ) OR ( data tracking algorithm ))))', query time: 0.12s Refine Results
  1. 101

    A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

    Published 2022
    “…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. …”
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  6. 106

    TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

    Published 2020
    “…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
  7. 107

    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. …”
  8. 108
  9. 109

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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    article
  10. 110

    Robust control of sampled data systems by Al-Sunni, F.M.

    Published 1998
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are given for demonstration…”
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    article
  11. 111

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
    Get full text
    article
  12. 112

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
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    article
  13. 113

    Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

    Published 2015
    “…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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    article
  14. 114

    Stochastic Search Algorithms for Exam Scheduling by Mansour, Nashat

    Published 2007
    “…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …”
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    article
  15. 115
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    Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

    Published 2020
    “…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. …”
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  17. 117

    Data Redundancy Management in Connected Environments by Mansour, Elio

    Published 2020
    “…We describe its modules, and clustering-based algorithms. Moreover, our proposal detects temporal, and spatial-temporal redundancies in order to consider both static and mobile devices/sensors. …”
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  18. 118

    Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

    Published 2022
    “…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”
  19. 119

    Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

    Published 2022
    “…<p>Resistance to differential cryptanalysis is a fundamental security requirement for symmetric block ciphers, and recently, deep learning has attracted the interest of cryptography experts, particularly in the field of block cipher cryptanalysis, where the bulk of these studies are differential distinguisher based black-box attacks. This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”
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