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يعرض 121 - 140 نتائج من 461 نتيجة بحث عن '(((( data processing algorithm ) OR ( deep learning algorithm ))) OR ( element network algorithm ))', وقت الاستعلام: 0.15s تنقيح النتائج
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    Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب Odat, Alhaj-Saleh A.

    منشور في 2024
    "…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…"
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    Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

    منشور في 2023
    "…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"
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    Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

    منشور في 2023
    "…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"
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  8. 128

    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing حسب Jincheng Zhou (1887307)

    منشور في 2023
    "…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …"
  9. 129

    Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

    منشور في 2025
    "…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …"
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    A fast exact sequential algorithm for the partial digest problem حسب Mostafa M. Abbas (17058093)

    منشور في 2016
    "…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …"
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    Use of Data Mining Techniques to Detect Fraud in Procurement Sector حسب AL HAMMADI, SUMAYYA ABDULLA

    منشور في 2022
    "…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …"
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    A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks حسب Sakib Mahmud (15302404)

    منشور في 2025
    "…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …"
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    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

    منشور في 2025
    "…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …"
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    article