يعرض 1 - 20 نتائج من 723 نتيجة بحث عن '(((( implementing finding algorithm ) OR ( element data algorithms ))) OR ( data using algorithm ))', وقت الاستعلام: 0.15s تنقيح النتائج
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    A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) حسب Wehbe, Gioia Wahib

    منشور في 2016
    "…In addition, implementing feasible computational methods for such enormous data is by itself another challenge. …"
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    masterThesis
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    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering حسب Abu Zitar, Raed

    منشور في 2022
    "…The main idea of applying OLB and LF is to improve the traditional AOA exploration and exploitation trends in order to find the best clusters. To evaluate the AAOA, we implemented extensive experiments using twenty-three well-known benchmark functions and eight data clustering datasets. …"
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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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    Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant حسب Shahbaz Hussain (9765320)

    منشور في 2019
    "…The results are of great significance as the real data of an IPP is used and imply that the performance of PSO is better than that of GA in case of CEED for finding the optimal solution concerning fuel cost, emission, convergence characteristics, and computational time. …"
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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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    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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    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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    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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    article
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