Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. حسب Borjan Milinkovic (21349908)

Code snippets to add user-specific custom functionality in PyNoetic. حسب Gursimran Singh (575288)

الموضوعات:

Study proposed algorithm. حسب Ainhoa Pérez-Guerrero (21377457)

"…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …"

Elementary effects (EE) results for the generation of villous vessels within a placentone employing the input parameter ranges from Table 1. حسب Diana C. de Oliveira (9220729)

Modular architecture design of PyNoetic showing all its constituent functions. حسب Gursimran Singh (575288)

الموضوعات:

Friedman test average rankings of IFOX and competing optimization algorithms across CL, C17, C19, C21, C22, and RWPs. The “Position” column indicates the overall rank based on the... حسب Mahmood A. Jumaah (22272371)

Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx حسب Peng Liu (120506)

"…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). …"

Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff حسب Peng Liu (120506)

"…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). …"

Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff حسب Peng Liu (120506)

"…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). …"

Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff حسب Peng Liu (120506)

"…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). …"

Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff حسب Peng Liu (120506)

"…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). …"

Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff حسب Peng Liu (120506)

"…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). …"

Multi-algorithm comparison figure. حسب Dawei Wang (471687)

"…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"

System no-load torque response results under three control algorithms. حسب Haoran Cui (7235234)

الموضوعات:

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. حسب Gursimran Singh (575288)

الموضوعات:

Trajectory comparison for system 3: (A) starting point within collection range; (B) starting point outside collection range. حسب Jingnan Yan (20727331)

Trajectory comparison for system 1: (A) starting point within collection range; (B) starting point outside collection range. حسب Jingnan Yan (20727331)

Trajectory comparison for system 2: (A) starting point within collection range; (B) starting point outside collection range. حسب Jingnan Yan (20727331)

Schematic diagram of sliding mode variable structure control algorithm design content. حسب Haoran Cui (7235234)

الموضوعات:

Average Friedman test ranks (left) and pairwise average Wilcoxon signed-rank test p-values (right) for all compared optimization algorithms across CL, C17, C19, C21, C22, and RWPs. حسب Mahmood A. Jumaah (22272371)