Iteration curve of the optimization process. by Meijun Shang (22806461)

“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”

Table_1_Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.docx by Jiajin He (13386702)

Supplementary file 1_Machine learning algorithms to predict epidural-related maternal fever: a retrospective study.docx by Xiaohui Guo (131711)

LSTM model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”

MLP Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”

RNN Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”

CNN Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx by Xinping Lin (1591438)

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

Business priorities. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

Topology of 14-node communication network. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

Routing policy based on path satisfaction. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

Changes of risk value under different parameters. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

Performance of active and standby paths. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

DATA. by Yang Yu (4292)

“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”

CNN-LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Data_Sheet_1_Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis.pdf by Mikhail Ya Yadgarov (18543769)

Table_1_Optimal Reopening Pathways With COVID-19 Vaccine Rollout and Emerging Variants of Concern.pdf by Yanyu Xiao (682443)

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

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation. by Aly A. Valliani (13251484)

“…<p><b>(A)</b> There are four primary methods by which machine learning models can be deployed in a context with distinct data domains: 1) train a model on one domain and deploy it across multiple distinct domains, 2) train multiple bespoke models that are optimized for deployment on individual domains, 3) train and deploy a single global model on all domains, and 4) train a model on one domain and adapt it through technical means to make it performant on a distinct domain. …”

Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”