The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

Parameter optimization results of the RF model improved by FCM clustering. by Xini Fang (20861990)

The confusion matrix for six algorithmic models. by Chan Xu (1510759)

Case 1: PADR evaluation without scheduling. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Case 2: PADR with load scheduling. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

SPVE hourly varying irradiance. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Hourly varying ambient temperature. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Estimated SPVE generation. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Case 2: Hourly scheduled load profile. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Storage batteries charging level. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

Utility pricing scheme. by Hisham Alghamdi (20114096)

“…<div><p>Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. …”

The primary composite outcome between the propensity matched Bebtelovimab (BEB) monoclonal antibody (MAb) and untreated control groups. by Srilekha Sridhara (15374444)

Subjects:

The robustness test results of the model. by Xini Fang (20861990)

“…Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”

Construction process of RF. by Xini Fang (20861990)

“…Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”

Data_Sheet_1_A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions.PDF by Leon Lufkin (11276856)

Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.X... by Fang Tian (360682)

Image_1_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Patients... by Mingxue Yu (10273496)

Data_Sheet_1_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Pat... by Mingxue Yu (10273496)

Time complexity of different safety algorithms. by Most. Fatematuz Zohora (19429152)

“…Unlike conventional methods, the DBDAA dynamically includes processes in safety checks, considerably decreasing the number of comparisons required to determine safe states. This optimization reduces the time complexity to O(n) in the best-case and O(<i>nd</i>) in the average and worst-case scenarios, compared to the O(<i>n</i>²<i>d</i>) complexity of the original Banker’s algorithm. …”

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