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

“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

Total primary energy demand by fuel in China. by Da Lian (18880882)

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Optimized model prediction performance. by Guang Tu (22054865)

Study case/patient distribution algorithm. by Navid Behzadi Koochnai (18554931)

S1 Data - by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Curve of step response signal of 6 algorithms. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Weights of sample data. by Yixuan Lu (9987980)

Models’ performance without optimization. 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. …”

Sample data of K-means clustering. by Yixuan Lu (9987980)

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. …”

Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf by Yuwen Lyu (14330781)

“…</p>Method<p>Patient medical decision-making tendencies were predicted by primary survey data obtained from 248 participants at third-level grade-A hospitals in China. …”

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

RNN performance comparison with/out optimization. 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. …”

Proposed reinforcement learning architecture. by Enoch Solomon (21416703)

“…Experimental evaluation were conducted employing Deep Q Networks (DQN) and Proximal Policy Optimization (PPO) algorithms within ViZDoom and Unity reinforcement learning environments. …”

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

Data_Sheet_1_Construction and Interpretation of Prediction Model of Teicoplanin Trough Concentration via Machine Learning.docx by Pan Ma (400070)

Table_8_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”