Search alternatives:
learning algorithm » learning algorithms (Expand Search)
means algorithm » search algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data learning » deep learning (Expand Search)
Showing 261 - 280 results of 728 for search '(( elements means algorithm ) OR ((( data learning algorithm ) OR ( data using algorithm ))))', query time: 0.13s Refine Results
  1. 261

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
    Get full text
    article
  2. 262

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
    Get full text
    article
  3. 263
  4. 264

    A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

    Published 2022
    “…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …”
  5. 265

    Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

    Published 2023
    “…Considering these shortcomings, computational methods especially machine learning and deep learning algorithms are leveraged as an alternative to accelerate the accurate detection of CT scans as cancerous, and non-cancerous. …”
  6. 266

    Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

    Published 2023
    “…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
  7. 267

    Data Redundancy Management in Connected Environments by Mansour, Elio

    Published 2020
    “…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  8. 268

    Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review by Rehaan Hussain (22302742)

    Published 2025
    “…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
  9. 269

    R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks by Tamer Ahmed Eltaras (22565414)

    Published 2025
    “…<p dir="ltr">Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. …”
  10. 270

    Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

    Published 2025
    “…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”
  11. 271
  12. 272
  13. 273

    Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

    Published 1994
    “…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
    Get full text
    Get full text
    Get full text
    article
  14. 274

    Mapping realistic data sets on parallel computers by Mansour, N.

    Published 1993
    “…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  15. 275

    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.…”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  16. 276
  17. 277

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

    Published 2024
    “…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
    Get full text
  18. 278

    New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

    Published 2018
    “…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  19. 279

    The Effects of Data Mining on Small Businesses in Dubai by AlMutawa, Rasha

    Published 2011
    “…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …”
    Get full text
  20. 280

    Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

    Published 2019
    “…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”