بدائل البحث:
algorithm machine » algorithm achieves (توسيع البحث), algorithm within (توسيع البحث)
machine function » achieve functions (توسيع البحث), sine function (توسيع البحث)
algorithm machine » algorithm achieves (توسيع البحث), algorithm within (توسيع البحث)
machine function » achieve functions (توسيع البحث), sine function (توسيع البحث)
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Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip
منشور في 2025"…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …"
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Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx
منشور في 2025"…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …"
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83
Test results of multimodal benchmark functions.
منشور في 2025"…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …"
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84
Fixed-dimensional multimodal reference functions.
منشور في 2025"…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …"
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85
Test results of multimodal benchmark functions.
منشور في 2025"…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …"
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Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff
منشور في 2025"…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …"
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The structure of genetic algorithm (GA).
منشور في 2024"…First, physico-chemical inputs as bulk density (BD), initial water content (W<sub>i</sub>), saturated water content (W<sub>s</sub>), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …"
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