Algorithms and evaluation metrics integrated in the COPS framework. حسب Teemu J. Rintala (19333003)

Distributions of model parameters mirror differentially expressed ion channel genes. حسب Daniele Linaro (227790)

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx حسب Xinping Lin (1591438)

The parameter settings of the RF algorithm after parameter optimization. حسب Xini Fang (20861990)

Parameter optimization results of the RF model improved by FCM clustering. حسب Xini Fang (20861990)

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx حسب Liyin Zhang (6371999)

Evaluation metrics of the models’ performance. حسب Guangwei Liu (181992)

Pseudocode of artificial dragonfly algorithm. حسب Ghassan Ahmed Ali (17041488)

الموضوعات:

Features selected by optimization algorithms. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

The Hopfield artificial neural network algorithm. حسب Ghassan Ahmed Ali (17041488)

الموضوعات:

Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention. حسب Nicole Fraser-Hurt (2636833)

Optimized model prediction performance. حسب Guang Tu (22054865)

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis حسب Qing Hu (152962)

"…Machine learning analysis revealed significant influences of catalyst type, catalyst concentration, and the ratio of aldehyde-to-ketone on reaction efficiency. A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …"

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis حسب Qing Hu (152962)

"…Machine learning analysis revealed significant influences of catalyst type, catalyst concentration, and the ratio of aldehyde-to-ketone on reaction efficiency. A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …"

Data used to drive the Double Layer Carbon Model in the Qinling Mountains. حسب Huiwen Li (17705280)

"…The DLCM defines four soil carbon pools, categorized based on their location within the soil profile and their decomposition rates. The model divides the soil profile into topsoil (0-20 cm) and subsoil (20–100 cm) layers to match the SOC maps of the corresponding two layers generated by data-driven models. …"

Data_Sheet_1_How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework.ZIP حسب Hao Wu (65943)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx حسب Çaǧlar Çaǧlayan (12253934)

Côte d’Ivoire model outputs on actual and optimized 2016 spending and impact by care delivery platform. حسب Nicole Fraser-Hurt (2636833)

Training error and accuracy for all HNN models. حسب Ghassan Ahmed Ali (17041488)

الموضوعات:

Implementation time performance of various HNN-EBkSAT models. حسب Ghassan Ahmed Ali (17041488)

الموضوعات: