يعرض 1 - 20 نتائج من 716 نتيجة بحث عن '(( data using algorithm ) OR ((( develop deep algorithm ) OR ( element data algorithm ))))', وقت الاستعلام: 0.18s تنقيح النتائج
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    Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment حسب Zakaria Tolba (16904718)

    منشور في 2022
    "…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"
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    Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence حسب Al Rayhi, Nasser

    منشور في 2020
    "…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …"
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    Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

    منشور في 2021
    "…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …"
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    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

    منشور في 2021
    "…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …"
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    Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm حسب Abu Zitar, Raed

    منشور في 2022
    "…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …"
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    Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب Ali Jassim Lari (22597940)

    منشور في 2025
    "…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …"
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    Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques حسب Abu Zitar, Raed

    منشور في 2022
    "…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …"
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    Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

    منشور في 2022
    "…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …"
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    A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

    منشور في 2003
    "…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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    article
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    Data reductions and combinatorial bounds for improved approximation algorithms حسب Abu-Khzam, Faisal N.

    منشور في 2016
    "…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …"
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    article
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