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Showing 21 - 40 results of 159 for search '(( data selection algorithm ) OR ( data injection algorithm ))', query time: 0.10s Refine Results
  1. 21

    A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

    Published 2016
    “…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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    masterThesis
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    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. …”
  4. 24

    Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

    Published 2025
    “…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
  5. 25

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

    Published 2022
    “…Adopting a random selection strategy would entail substantial problems due to the heterogeneity in terms of data quality, and computational and communication resources across the participants. …”
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    masterThesis
  6. 26

    Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

    Published 2022
    “…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
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    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

    Published 2023
    “…The SVM hyperparameters were optimized simultaneously with feature selection, and the model was tested with test data. …”
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    Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

    Published 2024
    “…The aim is to demonstrate the robustness of the proposed algorithms in effectively identifying telnet, password, distributed denial of service (DDoS), injection, and backdoor vulnerabilities in IoT ecosystems. …”
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    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. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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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
    “…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”
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    Parallel genetic algorithm for disease-gene association by Mansour, Nashat

    Published 2011
    “…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…”
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    conferenceObject
  20. 40

    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…This paper surveys the published papers in PSO algorithms. Twenty research papers are analyzed and classified according to the implementation area used by the PSO algorithm (neural networks, feature selection, and data clustering). …”
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