يعرض 81 - 100 نتائج من 182 نتيجة بحث عن '(((( elements search algorithm ) OR ( complex data algorithm ))) OR ( level coding algorithm ))', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 81

    Single channel speech denoising by DDPG reinforcement learning agent حسب Sania Gul (18272227)

    منشور في 2025
    "…<p dir="ltr">Speech denoising (SD) covers the algorithms that suppress the background noise from the contaminated speech and improve its clarity. …"
  2. 82
  3. 83

    Boosting the visibility of services in microservice architecture حسب Ahmet Vedat Tokmak (17773479)

    منشور في 2023
    "…In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …"
  4. 84

    Blue collar laborers’ travel pattern recognition: Machine learning classifier approach حسب Aya Hasan Alkhereibi (17151070)

    منشور في 2021
    "…A pattern recognition model is applied to a revealed preference (RP) survey obtained from the Ministry of Transportation and Communication (MoTC) in Qatar for the travel diary for blue-collar workers. Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …"
  5. 85

    Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks حسب Amirhossein Taherpour (19273879)

    منشور في 2024
    "…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …"
  6. 86
  7. 87

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

    منشور في 2025
    "…Building on this foundation, the second algorithm extends this analytical approach to support high-dimensional input data, substantially enhancing its utility across complex real-world datasets. …"
  8. 88

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

    منشور في 2022
    "…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …"
    احصل على النص الكامل
  9. 89

    A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation حسب Kfouri, Ronald

    منشور في 2023
    "…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …"
    احصل على النص الكامل
    احصل على النص الكامل
    احصل على النص الكامل
    masterThesis
  10. 90

    Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles حسب Zainab Akhtar (15192184)

    منشور في 2024
    "…The MLNN observer, employing a modified back-propagation algorithm, is used for the quadrotor’s state estimation. …"
  11. 91

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

    منشور في 2025
    "…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …"
  12. 92

    Sentiment visualization of correlation of loneliness mapped through social intelligence analysis حسب Hurmat Ali Shah (18192889)

    منشور في 2024
    "…These interactive plots provide a holistic view of the distribution of themes and topics associated with loneliness, allowing experts to explore and interact with the data, gaining deeper insights into the complexities surrounding this issue.…"
  13. 93
  14. 94

    Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

    منشور في 2024
    "…In this context, we formulate the problem as a non-linear programming (NLP) optimization problem aimed at maximizing the total EH IoT devices and determining the optimal trajectory paths for UAVs while adhering to the constraints related to the maximum time duration, the UAVs’ maximum energy consumption, and the minimum data rate to achieve a reliable transmission. Due to the complexity of the problem, the combinatorial nature of the formulated problem, and the difficulty of obtaining the optimal solution using conventional optimization problems, we propose a lightweight meta-RL solution capable of solving the problem by learning the system dynamics. …"
  15. 95

    Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

    منشور في 2025
    "…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …"
  16. 96
  17. 97

    Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks حسب Haris M. Khalid (17017743)

    منشور في 2023
    "…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …"
  18. 98

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

    منشور في 2020
    "…We study numerical computation of conformal invariants of domains in the complex plane. In particular, we provide an algorithm for computing the conformal capacity of a condenser. …"
    احصل على النص الكامل
    احصل على النص الكامل
    احصل على النص الكامل
    article
  19. 99

    Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials حسب Ghouti, Lahouari

    منشور في 1997
    "…However, the improved performance is achieved at the expense of higher computational complexity and data requirements.…"
    احصل على النص الكامل
    masterThesis
  20. 100