Search alternatives:
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
high process » high protein (Expand Search), high success (Expand Search), highly processed (Expand Search)
binary high » dietary high (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
high process » high protein (Expand Search), high success (Expand Search), highly processed (Expand Search)
binary high » dietary high (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
-
41
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. …”
-
42
-
43
-
44
-
45
-
46
-
47
Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
Published 2020“…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”
-
48
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…The spectral data were split into a training set (80%) and an external validation set (20%). For binary variables, the classification accuracy for cassava cooking time was notably high (RCal2 ranging from 0.72 to 0.99). …”
-
49
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…The spectral data were split into a training set (80%) and an external validation set (20%). For binary variables, the classification accuracy for cassava cooking time was notably high (RCal2 ranging from 0.72 to 0.99). …”
-
50
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.…”
-
51
Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx
Published 2024“…The results of this study lead the authors to recommend formulating a family-centered policy for migrant workers to reside in urban areas, optimizing the allocation of medical resources and public services, and improving family urban integration among migrant workers in order to avoid mental health problems in the process of urban integration.…”
-
52
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”