Search alternatives:
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
binary basic » binary mask (Expand Search)
primary data » primary care (Expand Search)
basic joint » based joint (Expand Search)
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
binary basic » binary mask (Expand Search)
primary data » primary care (Expand Search)
basic joint » based joint (Expand Search)
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Study cohort selection.
Published 2023“…The study cohorts were 1:1 propensity matched without replacement across 26 covariates using an optimal matching algorithm that minimizes the sum of absolute pairwise distance across the matched sample after fitting and using logistic regression as the distance function. …”
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Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change"
Published 2025“…The process includes (1) harmonizing Landsat 5, 7, 8, and Sentinel-2 data using the HLS algorithm, and (2) filling temporal gaps with an optimized object-based STARFM fusion algorithm. …”
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Confusion matrix for multiclass classification.
Published 2025“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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General flow chart of the proposed method.
Published 2025“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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Data used to drive the Double Layer Carbon Model in the Qinling Mountains.
Published 2024“…It relies on comprehensive input data, including initial SOC stocks, climate data, and vegetation production to drive these simulations.…”
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Results of Comprehensive weighting.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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The prediction error of each model.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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VIF analysis results for hazard-causing factors.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Benchmark function information.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Geographical distribution of the study area.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Results for model hyperparameter values.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Flow chart of this study.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Stability analysis of each model.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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Robustness Analysis of each model.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”