يعرض 81 - 100 نتائج من 133 نتيجة بحث عن '(( implement learning algorithm ) OR ((( relevant data algorithm ) OR ( element te algorithm ))))', وقت الاستعلام: 0.11s تنقيح النتائج
  1. 81

    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

    منشور في 2023
    "…Here, the Quantized Identical Data Imputation (QIDI) mechanism is implemented at first for data preprocessing and normalization. …"
  2. 82

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

    منشور في 2023
    "…These assessments can be performed by means of a live health-check service, or, alternatively, by making a prediction of the current state of affairs with the application of machine learning-based approaches. 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. …"
  3. 83

    Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review حسب Zainab Jan (17306614)

    منشور في 2023
    "…PubMed, Google Scholar, Science Direct, BioRXiv, and MedRxiv were explored to identify relevant articles. Study selection and data extraction were independently conducted by 2 reviewers. …"
  4. 84

    Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices حسب Neder Karmous (19743430)

    منشور في 2024
    "…This SDN-ML-IoT uses a Machine Learning (ML) method in a Software-Defined Networking (SDN) environment in order to protect smart home IoT devices from DDoS attacks. …"
  5. 85

    Nested ensemble selection: An effective hybrid feature selection method حسب Kamalov, Firuz

    منشور في 2023
    "…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …"
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    article
  6. 86
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  8. 88

    An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System حسب Alkhatib, Osama

    منشور في 2019
    "…Two types of machine learning models namely classification and regression model were developed and implemented to predict the failure and abnormal behavior of the system. …"
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  9. 89

    Toward automatic motivator selection for autism behavior intervention therapy حسب Siyam, Nur

    منشور في 2022
    "…The states, actions and rewards design consider the factors that impact the efectiveness of a motivator based on applied behavior analysis as well as learners’ individual preferences. We use a Q-learning algorithm to solve the modeled problem. Our proposed solution is then implemented as a mobile application developed for special education plans coordination. …"
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  10. 90

    Cooperative Caching Policy in Fog Computing for Connected Vehicles حسب Ghazleh, Ali

    منشور في 2023
    "…In this thesis, we implemented cooperation between a Deep Reinforcement Learning (DRL) model and Federated Learning to improve caching in Connected Vehicles connected to fog nodes. …"
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    masterThesis
  11. 91

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

    منشور في 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. …"
  12. 92

    Exploring New Parameters to Advance Surface Roughness Prediction in Grinding Processes for the Enhancement of Automated Machining حسب Mohammadjafar Hadad (21142499)

    منشور في 2024
    "…Recent studies have concentrated on the development of neural networks, as a subcategory of machine learning techniques, to predict non-linear roughness behavior in relation to various parameters. …"
  13. 93

    An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems حسب Abdel-Salam, Mahmoud

    منشور في 2024
    "…Several metaheuristics, such as the Genghis Khan Shark Optimizer Algorithm (GKSO), can assist in optimizing the FS issue. …"
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  14. 94

    Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective حسب Zhitao Xu (2426023)

    منشور في 2024
    "…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"
  15. 95

    Automated skills assessment in open surgery: A scoping review حسب Hawa Hamza (17707224)

    منشور في 2025
    "…About 35 % utilized deep learning algorithms, specifically convolutional neural networks (CNN) (<i>n </i>= 14). …"
  16. 96
  17. 97

    A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System حسب Ekinci, Serdar

    منشور في 2023
    "…We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. …"
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  18. 98
  19. 99

    Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring حسب Aya Nabil Sayed (17317006)

    منشور في 2024
    "…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …"
  20. 100