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Showing 121 - 140 results of 407 for search '(( element method algorithm ) OR ((( data combined algorithm ) OR ( data processing algorithm ))))', query time: 0.13s Refine Results
  1. 121
    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts

    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

    Published 2022
    “…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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  2. 122
    Data redundancy management for leaf-edges in connected environments

    Data redundancy management for leaf-edges in connected environments by Mansour, Elio

    Published 2022
    “…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …”
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  3. 123
    Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

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

    Published 2023
    “…Researchers have utilized diverse data sources, such as citations, metadata, content, and hybrids, in their approaches.In these sources, the meta-data-based approach stands out for research paper classification due to its availability at no cost. …”
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  4. 124
    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information

    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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  5. 125
    Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements

    Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements by Stefano Nardean (14151900)

    Published 2023
    “…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. …”
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  6. 126
    Big Data Energy Management, Analytics and Visualization for Residential Areas

    Big Data Energy Management, Analytics and Visualization for Residential Areas by Gupta, Ragini

    Published 2020
    “…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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  7. 127
    Using genetic algorithms to optimize software quality estimation models

    Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

    Published 2004
    “…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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  8. 128
    Exploring Semi-Supervised Learning Algorithms for Camera Trap Images

    Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

    Published 2022
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  9. 129
    An efficient approach for textual data classification using deep learning

    An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

    Published 2022
    “…Textual data contains much useless information that must be pre-processed. …”
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  10. 130
    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm

    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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  11. 131
    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
    “…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
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  12. 132
    Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory

    Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

    Published 2025
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  13. 133
    Convergence and steady-state analysis of the normalized least mean fourth algorithm

    Convergence and steady-state analysis of the normalized least mean fourth algorithm by Zerguine, Azzedine

    Published 2007
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  14. 134
    Convergence and steady-state analysis of the normalized least mean fourth algorithm

    Convergence and steady-state analysis of the normalized least mean fourth algorithm by Zerguine, Azzedine

    Published 2007
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  15. 135
    The buffered work-pool approach for search-tree based optimization algorithms

    The buffered work-pool approach for search-tree based optimization algorithms by Abu-Khzam, Faisal N.

    Published 2017
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  16. 136
    A method for optimizing test bus assignment and sizing for system-on-a-chip

    A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

    Published 2017
    “…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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  17. 137
    Assessment of static pile design methods and non-linear analysis of pile driving

    Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

    Published 2006
    “…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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  18. 138
    An ant colony optimization algorithm to improve software quality prediction models

    An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

    Published 2011
    “…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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  19. 139
    Evolutionary algorithms for state justification in sequential automatic test pattern generation

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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  20. 140
    The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs

    The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs by Muhammad Kashif (3923483)

    Published 2023
    “…This paper presents a framework designed to explore the interplay of multiple factors contributing to the BP problem in quantum neural networks (QNNs), which poses a critical challenge for the practical applications of QML. 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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