Showing 1 - 20 results of 24 for search '(((( implement forest algorithm ) OR ( element pass algorithm ))) OR ( neural coding algorithm ))', query time: 0.12s Refine Results
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    A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

    Published 2019
    “…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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    FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

    Published 2020
    “…The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. …”
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    A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

    Published 2025
    “…The paper uses naive Bayes, Support Vector Machine (SVM), and Random Forest (RF) as classifiers after careful investigation. …”
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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    Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

    Published 2024
    “…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”
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    An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

    Published 2019
    “…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …”
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