بدائل البحث:
4_using algorithm » routing algorithm (توسيع البحث), using algorithms (توسيع البحث), twisting algorithm (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
image 4_using » image 1_using (توسيع البحث), image 2_using (توسيع البحث), image 3_using (توسيع البحث)
element data » settlement data (توسيع البحث), relevant data (توسيع البحث), movement data (توسيع البحث)
4_using algorithm » routing algorithm (توسيع البحث), using algorithms (توسيع البحث), twisting algorithm (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
image 4_using » image 1_using (توسيع البحث), image 2_using (توسيع البحث), image 3_using (توسيع البحث)
element data » settlement data (توسيع البحث), relevant data (توسيع البحث), movement data (توسيع البحث)
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Comparison of different optimization algorithms.
منشور في 2025الموضوعات: "…crayfish optimization algorithm…"
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Algorithmic experimental parameter design.
منشور في 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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Image 4_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
منشور في 2025"…<p>Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables from pure larch (LP), birch (BP), and mixed larch-birch (LB) forests in the mountainous region of northern Hebei, China, this study employed random forest (RF) algorithms to evaluate the relative importance and partial dependence of biotic and abiotic factors on stand volume growth. …"
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Spatial spectrum estimation for three algorithms.
منشور في 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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The run time for each algorithm in seconds.
منشور في 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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Risk element category diagram.
منشور في 2025"…This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …"
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Scatter diagram of different principal elements.
منشور في 2025"…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …"
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List of the time used by each algorithm.
منشور في 2024"…To this end, this paper proposes an entropy-based dynamic ensemble classification algorithm (EDAC) to consider data streams with class imbalance and concept drift simultaneously. …"
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Sanitized databases using MLHProtector algorithm.
منشور في 2025"…<div><p>Privacy is as a critical issue in the age of data. Organizations and corporations who publicly share their data always have a major concern that their sensitive information may be leaked or extracted by rivals or attackers using data miners. …"
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