Iteration curve of the optimization process. حسب 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. …"

The prediction error of each model. حسب Hao Yang (328526)

"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"

Results for model hyperparameter values. حسب Hao Yang (328526)

"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"

Stability analysis of each model. حسب Hao Yang (328526)

"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"

Robustness Analysis of each model. حسب Hao Yang (328526)

"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"

Error of ICESat-2 with respect to airborne data. حسب Qinghua Li (398885)

"…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …"

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

The workflow of the proposed model. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Multivariable Cox proportional hazard model^b'*' for the composite outcome among the post-propensity matched COVID-19 infected patients in the Banner Healthcare System be... حسب Srilekha Sridhara (15374444)

LSTM model performance. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

MLP Model performance. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

RNN Model performance. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

CNN Model performance. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation. حسب 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. …"

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

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. …"

S2 Data - حسب Musab A. Isak (18824223)

S1 Data - حسب Musab A. Isak (18824223)

Data_Sheet_1_Optimizing Spatio-Temporal Allocation of the COVID-19 Vaccine Under Different Epidemiological Landscapes.pdf حسب Wen Cao (696121)

Business priorities. حسب Yang Yu (4292)

"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"