بدائل البحث:
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary mask » binary image (توسيع البحث)
mask driven » mapk driven (توسيع البحث), task derived (توسيع البحث), hastv driven (توسيع البحث)
lens » less (توسيع البحث)
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary mask » binary image (توسيع البحث)
mask driven » mapk driven (توسيع البحث), task derived (توسيع البحث), hastv driven (توسيع البحث)
lens » less (توسيع البحث)
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1
Lens imaging opposition-based learning.
منشور في 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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2
Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens
منشور في 2021"…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …"
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3
Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens
منشور في 2021"…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …"
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4
Compare algorithm parameter settings.
منشور في 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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5
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6
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7
-value on CEC2022 (dim = 20).
منشور في 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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8
Precision elimination strategy.
منشور في 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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9
Results of low-light image enhancement test.
منشور في 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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10
-value on 23 benchmark functions (dim = 30).
منشور في 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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11
Evaluation metrics obtained by SBOA and MESBOA.
منشور في 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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12
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14
adjoint-elastic-registration.zip from Organ registration from partial surface data in augmented surgery from an optimal control perspective
منشور في 2023"…The resulting optimization problem features an elastic model, a least-squares data attachment term based on orthogonal projections, and an admissible set of surface loads defined prior to reconstruction in the mechanical model. …"
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15
Massive Mixed Models in Julia
منشور في 2025"…<br><br>Although we are already very excited to be able to fit such large models at all, we want to fit them even faster. Julia enables us to continue algorithmic development in a coherent way. …"
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16
Parameter settings.
منشور في 2025"…<div><p>This study aims to enhance the recommendation system’s capability in addressing cold start issues, semantic understanding, and modeling the diversity of user interests. The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …"
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17
Fusion framework.
منشور في 2025"…<div><p>This study aims to enhance the recommendation system’s capability in addressing cold start issues, semantic understanding, and modeling the diversity of user interests. The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …"
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18
Generation steps of user profiles.
منشور في 2025"…<div><p>This study aims to enhance the recommendation system’s capability in addressing cold start issues, semantic understanding, and modeling the diversity of user interests. The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …"
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19
Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty
منشور في 2021"…The central questions are: How do we optimally learn from data through the lens of models? …"
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20
SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
منشور في 2020"…The central questions are: How do we optimally learn from data through the lens of models? …"