Surround Suppression mechanism. by Elnaz Nemati (21402730)

A portfolio selection model based on the knapsack problem under uncertainty by Fereshteh Vaezi (6655028)

“…The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. …”

DEM error verified by airborne data. by 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. …”

Error of models. by 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. …”

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)

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. …”

The prediction error of each model. by 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. by 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. by 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. by 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. by 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 by Mikhail Ya Yadgarov (18543769)

The workflow of the proposed model. by 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... by Srilekha Sridhara (15374444)

LSTM model performance. by 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. by 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. by 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. by 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. 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. …”

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