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Showing 1 - 20 results of 713 for search '(( elements network algorithm ) OR ((( path model algorithm ) OR ( data using algorithm ))))', query time: 0.12s Refine Results
  1. 1

    A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

    Published 2003
    “…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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    A method for data path synthesis using neural networks by Harmanani, H.

    Published 2017
    “…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
    “…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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    Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

    Published 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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    Allocation and re-allocation of data in a grid using an adaptive genetic algorithm by Mansour, N.

    Published 2006
    “…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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    Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

    Published 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 by Abu Zitar, Raed

    Published 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 by Ali Jassim Lari (22597940)

    Published 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 by Usman Ali (6586886)

    Published 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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    Data reductions and combinatorial bounds for improved approximation algorithms by Abu-Khzam, Faisal N.

    Published 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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    Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

    Published 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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    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    “…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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