Search alternatives:
active optimization » acid optimization (Expand Search), objective optimization (Expand Search), reaction optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based active » based practice (Expand Search), based activity (Expand Search)
sample model » simple model (Expand Search), sample level (Expand Search)
active optimization » acid optimization (Expand Search), objective optimization (Expand Search), reaction optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based active » based practice (Expand Search), based activity (Expand Search)
sample model » simple model (Expand Search), sample level (Expand Search)
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
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QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
Published 2020“…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
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Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
Published 2022“…<p>It is of great practical and theoretical significance to identify driver fatigue state in real time and accurately and provide active safety warning in time. In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”
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Summary of existing CNN models.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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Testing results for classifying AD, MCI and NC.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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MCLP_quantum_annealer_V0.5
Published 2025“…<p dir="ltr">Geospatial optimization problems are fundamental research issues in geographic information science modeling, characterized by high dimensionality, dynamics, and discreteness. …”
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Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
Published 2020“…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
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Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model
Published 2025“…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …”
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Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
Published 2025“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”