Showing 81 - 100 results of 163 for search '(( test processing algorithm ) OR ((( element data algorithm ) OR ( neural coding algorithm ))))', query time: 0.12s Refine Results
  1. 81
  2. 82

    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

    Published 2022
    “…In addition, it implies carrying out the training and testing process in each phase. Since the best model is obtained from training, each time it is performed for a given phase, the model is adjusted to detect new attacks. …”
    Get full text
  3. 83

    Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

    Published 2021
    “…Multiple tree-based machine learning algorithms are tested with parallel computation to evaluate the performance with tunable parameters on a real-world dataset. …”
  4. 84
  5. 85

    A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

    Published 2025
    “…Most improved RF versions modify attribute selection processes or combine them with other machine learning algorithms, increasing their complexity. …”
  6. 86
  7. 87

    Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

    Published 2021
    “…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
  8. 88
  9. 89

    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

    Published 2021
    “…The accuracy of the proposed modeling is tested on a 1,000-transformer substation subset of the Spanish distribution electrical network data containing more than 24 million load records. …”
  10. 90
  11. 91

    Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements by Emara-Shabaik, Husam

    Published 2020
    “…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …”
    Get full text
    article
  12. 92
  13. 93
  14. 94

    Loop based scheduling for high level synthesis by Al-Sukhni, H.F.

    Published 1995
    “…This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. …”
    Get full text
    Get full text
    article
  15. 95

    Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by Abhishek Raj (7245425)

    Published 2025
    “…Additionally, the computational efficiency of the algorithm is evidenced by an average processing time of 0.0764 seconds per fault event, making it well-suited for real-time applications.…”
  16. 96

    Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks by Mohamed Massaoudi (16888710)

    Published 2024
    “…The proposed algorithm is evaluated on the 68-bus system and the Northeastern United States 25k-bus synthetic test system with credible contingencies using the PowerWorld simulator. …”
  17. 97

    A hybrid approach for XML similarity by Tekli, Joe

    Published 2007
    “…Various algorithms for comparing hierarchically structured data, e.g. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  18. 98
  19. 99

    On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

    Published 2017
    “…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  20. 100