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Showing 1 - 6 results of 6 for search '(((( complement mean algorithm ) OR ( complement coa algorithm ))) OR ( neural cosine algorithm ))', query time: 0.08s Refine Results
  1. 1
    Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm

    Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

    Published 2023
    “…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”
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  2. 2
    Face Recognition in Uncontrolled Indoor Environment

    Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

    Published 2013
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    doctoralThesis
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  3. 3
    Establishing Autonomous AUS-Quadrotor

    Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

    Published 2009
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    doctoralThesis
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  4. 4
    Automatic White Blood Cell Differential Classification

    Automatic White Blood Cell Differential Classification by Al-Muhairy, Juma A. Bin Darwish

    Published 2005
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    doctoralThesis
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  5. 5
    Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review

    Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review by Loay A. Salman (14150322)

    Published 2023
    “…</p><h3>Results</h3><p dir="ltr">A total of four observational studies comprised of at least 34,547 patients were included in this review. A mean MINORS score of 11 out of 16 was assigned to the review. …”
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  6. 6
    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
    “…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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