بدائل البحث:
processing maximization » processing visualization (توسيع البحث)
maximization algorithm » optimization algorithms (توسيع البحث), classification algorithm (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
pairs processing » pre processing (توسيع البحث), ai processing (توسيع البحث), plasma processing (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
processing maximization » processing visualization (توسيع البحث)
maximization algorithm » optimization algorithms (توسيع البحث), classification algorithm (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
pairs processing » pre processing (توسيع البحث), ai processing (توسيع البحث), plasma processing (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
-
41
Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
-
42
Flow diagram of the automatic animal detection and background reconstruction.
منشور في 2020"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"
-
43
Seed mix selection model
منشور في 2022"…The model thus requires three types of data presented as matrices in order to calculate the maximum number of bee species supported by a given seed mix: 1) adult phenology of each bee species, where each cell represents whether or not that bee species was observed in the data during a given time period, 2) flowering phenology of plants, where each cell represents whether or not a bee was collected from that plant species during a given time period, and 3) pairwise interactions between plant species and bee species, where each cell represents whether each plant-bee species pair was observed interacting in the data.</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …"
-
44
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</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.…"