Optimized model prediction performance. حسب Guang Tu (22054865)

The structure of genetic algorithm (GA). حسب Ali Akbar Moosavi (17769033)

"…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. …"

Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models حسب Ping Hou (17213)

"…In this study, artificial neural network models are developed to predict chemical ecotoxicity (HC₅₀) based on experimental data to fill data gaps in a widely used database (USEtox). …"

Comparison statistics of different machine learning algorithms including MLP, GRNN, and RBF for modeling and predicting callogenesis rate and callus fresh weight of petunia. حسب Hamed Rezaei (11085366)

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. حسب Danish M. Anwer (15383441)

AUROC scores with 95% CI from Day 1 to Day 4 for different algorithms. حسب Armin Abdollahi (21440129)

Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions. حسب Jari Turkia (17912475)

الموضوعات:

Data-Driven Development of Heterogeneous Catalysts for Propane Dehydrogenation with Machine Learning and Metaheuristic Optimization حسب Jungmok Oh (14117464)

"…This paper presents a hybrid framework that combines ML models with a metaheuristic optimization algorithm, to explore improved heterogeneous catalysts for propane dehydrogenation (PDH). …"

Data-Driven Development of Heterogeneous Catalysts for Propane Dehydrogenation with Machine Learning and Metaheuristic Optimization حسب Jungmok Oh (14117464)

"…This paper presents a hybrid framework that combines ML models with a metaheuristic optimization algorithm, to explore improved heterogeneous catalysts for propane dehydrogenation (PDH). …"

Nutrient predictors of the model. حسب Jari Turkia (17912475)

الموضوعات:

Comparison of models performance metrics. حسب Mukhtar Ijaiya (18935122)

"…Merged demographic, clinic, pharmacy, and laboratory data were included as potential predictor variables in multiple models. …"

Comparison of model structures for personal nutrient effects. حسب Jari Turkia (17912475)

الموضوعات:

Correlation plot of matrix C_<i>b</i> that includes the estimated within-model and cross-model correlations of personal effects. حسب Jari Turkia (17912475)

الموضوعات:

Predictive model-building process. حسب Mukhtar Ijaiya (18935122)

"…Merged demographic, clinic, pharmacy, and laboratory data were included as potential predictor variables in multiple models. …"

Correlation plot of matrix C_<i>g</i> that includes the estimated within-model and cross-model correlations in level of dialysis treatment. حسب Jari Turkia (17912475)

الموضوعات:

Posterior predictive check (PPC) of the final nutritional effect model. حسب Jari Turkia (17912475)

الموضوعات:

Structure of the graphical model with general, treatment, and personal level nutrient effects. حسب Jari Turkia (17912475)

الموضوعات:

Data collection during the patients’ usual treatment routine. حسب Jari Turkia (17912475)

الموضوعات:

Community modeling. حسب Colton J. Lloyd (5484473)

A schematic view of the step-by-step computational approach in the current study. حسب Hamed Rezaei (11085366)