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Showing 141 - 160 results of 254 for search '(( element method algorithm ) OR ((( data encoding algorithm ) OR ( deep learning algorithm ))))*', query time: 0.12s Refine Results
  1. 141

    A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam (22304047)

    Published 2025
    “…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
  2. 142

    Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks by Bekir Sait Ciftler (17541801)

    Published 2021
    “…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”
  3. 143

    Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

    Published 2024
    “…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
  4. 144

    A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

    Published 2017
    “…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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    conferenceObject
  5. 145

    Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

    Published 2006
    “…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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    masterThesis
  6. 146

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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    article
  7. 147

    DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs by Bahareh Jafari (22501715)

    Published 2025
    “…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”
  8. 148
  9. 149

    Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

    Published 2025
    “…<p>Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EEG analysis, and facilitate tailored therapeutic strategies, addressing the complexities of epilepsy management. …”
  10. 150

    A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks by Yassine Himeur (14158821)

    Published 2022
    “…Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. …”
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  12. 152

    DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

    Published 2022
    “…Therefore, we proposed a Deep Reinforcement Learning (DRL) solution based on Deep Deterministic Policy Gradient (DDPG) algorithm to solve the highly complex SC problem by adjusting the BF weights and mirror orientations. …”
  13. 153

    Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

    Published 2024
    “…However, AI tools, for instance, Machine Learning (ML) and Deep Learning (DL), offer precise and well-timed solutions for disease detection, classification, and eradication. …”
  14. 154

    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

    Published 2022
    “…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”
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    Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

    Published 2020
    “…Conventional Building Energy Management methods suffer from a high dimensional and complex control environment. In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”
  17. 157

    YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

    Published 2025
    “…It has recently become increasingly popular to apply deep learning algorithms to the identification of ships in SAR images. …”
  18. 158

    Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

    Published 2019
    “…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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