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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
low functional » new functional (Expand Search), go functional (Expand Search), cog functional (Expand Search)
algorithm low » algorithm flow (Expand Search), algorithm co (Expand Search), algorithm allows (Expand Search)
algorithm 1 » algorithm _ (Expand Search), algorithms _ (Expand Search), algorithm 8217 (Expand Search)
1 function » _ function (Expand Search), a function (Expand Search)
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Details of the metaheuristic algorithms.
Published 2025“…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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Parameter settings for algorithms.
Published 2025“…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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Two-stage object detection algorithm process.
Published 2023“…Regressive Function, Multinomial Naive Bayes and Gaussian Naive Bayes Algorithms have lower prediction delay, as low as 0.01s. …”
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Comparative analysis of algorithms.
Published 2024“…This paper presents a novel storage optimization algorithm, dubbed LIRU (Low Interference Recently Used), which synthesizes the strengths of the LIRS (Low Interference Recency Set) and LRU (Least Recently Used) replacement algorithms. …”
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Compare algorithm parameter settings.
Published 2025“…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
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Low-Rank Covariance Function Estimation for Multidimensional Functional Data
Published 2020“…Despite the lack of a closed form, under mild assumptions, the proposed estimator can achieve unified theoretical results that hold for any relative magnitudes between the sample size and the number of observations per sample field, and the rate of convergence reveals the phase-transition phenomenon from sparse to dense functional data. Based on a new representer theorem, an ADMM algorithm is developed for the trace-norm regularization. …”
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Differential analysis between the high- and low-risk score groups and functional analyses of DEGs.
Published 2024Subjects: -
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Data_Sheet_1_Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography.docx
Published 2020“…<p>Resting-state functional connectivity (RSFC) has been generally assessed with functional magnetic resonance imaging (fMRI) thanks to its high spatial resolution. …”
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