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Showing 301 - 320 results of 430 for search '(( data models algorithm ) OR ((( develop rd algorithm ) OR ( elements network algorithm ))))', query time: 0.12s Refine Results
  1. 301

    Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

    Published 2024
    “…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO<sub>2</sub> solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO<sub>2</sub> absorption capacity. …”
  2. 302

    Performance Prediction Using Classification by MOOLIYIL, GITA

    Published 2019
    “…A comprehensive evaluation requires that multiple models with different algorithms were analyzed using key performance measures. …”
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  3. 303

    Automated skills assessment in open surgery: A scoping review by Hawa Hamza (17707224)

    Published 2025
    “…In this scoping review, we present the open surgeries and clinical settings where AI-based skill assessment has been applied, the kind of surgical data acquired for the AI-based algorithms, and the types of AI-based models used for automated skills assessment. …”
  4. 304

    Inferential sensing techniques in industrial applications by Shakil,, Muhammad

    Published 0007
    “…Real data from a boiler plant is used to develop the model. …”
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    masterThesis
  5. 305
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  7. 307

    Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

    Published 2022
    “…Upon drift detection, the classifica tion algorithm may reset its model or concurrently grow a new learning model. …”
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  8. 308

    Joint computing, communication and cost-aware task offloading in D2D-enabled Het-MEC by Abbas, Nadine

    Published 2022
    “…Furthermore, we propose a low-complexity algorithm that generates high performance results and can be applied for large-scale networks. …”
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    article
  9. 309

    Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine by Shomope, Ibrahim

    Published 2024
    “…The type of algorithm employed to predict drug release from liposomes plays an important role in affecting the accuracy. …”
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    article
  10. 310

    Adaptive controlled superconducting magnetic energy storage devices for performance enhancement of wind energy systems by Rania A., Turky

    Published 2023
    “…It depends mainly on the actuating error signal, and it has a variable step size of the CMPN. The detailed modeling of the whole system is presented, including measured wind speed data, detailed switching techniques, a drive train model of the turbine, and real SMESD. …”
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    article
  11. 311

    High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

    Published 2023
    “…We also show that such extension of the hypergeometric resummation algorithm is able to employ non-perturbative information like strong-coupling and large-order asymptotic data which are always used to accelerate the convergence. …”
  12. 312

    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

    Published 2023
    “…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
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    article
  13. 313

    Computation of conformal invariants by Mohamed M.S., Nasser

    Published 2020
    “…We compare the performance and accuracy to previous results in the cases when numerical data is available and also in the case of several model problems where exact results are available.…”
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    article
  14. 314

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

    Published 2023
    “…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”
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    article
  15. 315

    A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

    Published 2023
    “…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”
  16. 316

    Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

    Published 2021
    “…Overall, studies that used smaller data sets reported higher accuracy.</p><h3>Conclusions</h3><p dir="ltr">This paper examined multiple AI-based skin cancer detection models. …”
  17. 317

    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

    Published 2023
    “…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
  18. 318

    Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

    Published 2022
    “…The first part of the thesis considers the problem of data collection from time-constrained IoT devices through deploying a UAV with uplink NOMA. …”
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    masterThesis
  19. 319

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

    Published 2023
    “…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”
  20. 320

    Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

    Published 2022
    “…The two movies are Wahed Tani which translates to (someone else) and Amahom which translate to (their uncle), Three datasets were employed, and several categorization models were compared across them. Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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