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Showing 1 - 9 results of 9 for search '(( algorithm cl function ) OR ((( algorithm python function ) OR ( algorithm pre function ))))', query time: 0.08s Refine Results
  1. 1
    Genetic and heuristic algorithms for regrouping service sites. (c2000)

    Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

    Published 2000
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    masterThesis
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  2. 2
    Defense against adversarial attacks: robust and efficient compressed optimized neural networks

    Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

    Published 2024
    “…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. …”
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  3. 3
    Cortical EEG Source Localization of Focal Epilepsy

    Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

    Published 2017
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    doctoralThesis
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  4. 4
    Autonomous Robot Navigation Based On Recurrent Neural Networks

    Autonomous Robot Navigation Based On Recurrent Neural Networks by Al-Sagban, Mariam Qusai

    Published 2012
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    doctoralThesis
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  5. 5
    The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability

    The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability by Abd-El-barr, Mostafa

    Published 2003
    “…A fault tolerant network is able to function even in the presence of some faults in the network. …”
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  6. 6
    Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle

    Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

    Published 2025
    “…Furthermore, the reduction in sideslip angle, excellent traction through minimizing tire slip ratio, avoiding oversteering and understeering, and maintaining an acceptable range of energy optimization are demonstrated for DRL controllers, especially for the TD3 and CL TD3 algorithms.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Open Journal of Vehicular Technology<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/ojvt.2025.3606120" target="_blank">https://dx.doi.org/10.1109/ojvt.2025.3606120</a></p>…”
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  7. 7
    Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network

    Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

    Published 2020
    “…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO<sub>3</sub> on the performance of anaerobic digestion (AD) process. …”
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  8. 8
    Large language models for code completion: A systematic literature review

    Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

    Published 2024
    “…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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  9. 9
    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins

    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

    Published 2025
    “…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …”
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