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Showing 1 - 20 results of 9,726 for search '(( element _ algorithm ) OR ((( table 1_decoding algorithm ) OR ( data modelling algorithm ))))', query time: 0.45s Refine Results
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    Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

    Published 2024
    “…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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    Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

    Published 2024
    “…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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    Risk element category diagram. by Yao Hu (3479972)

    Published 2025
    “…It can be summarized that the algorithmic model has good accuracy and robustness. …”
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    The run time for each algorithm in seconds. by Edward Antonian (21453161)

    Published 2025
    “…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”
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    Genetic Algorithm IQA Data by Michael Anastasios Mardikes (21762611)

    Published 2025
    Subjects: “…Modelling and simulation…”
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    Scatter diagram of different principal elements. by Jizhong Wang (7441697)

    Published 2025
    “…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”
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    Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

    Published 2024
    “…The proposed method exploits the Hamming distance to define a family of probability mass functions to model the data. The elements of this family are then considered as kernels of a finite mixture model with an unknown number of components. …”