Image_2_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx by Liyin Zhang (6371999)

Load data or power demand. by M. Nasrallah (19066121)

Pseudo Code of RBMO. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

P-value on CEC-2017(Dim = 30). by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Memory storage behavior. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Elite search behavior. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Description of the datasets. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

S and V shaped transfer functions. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

S- and V-Type transfer function diagrams. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Collaborative hunting behavior. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Friedman average rank sum test results. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. variant comparison adaptation data. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

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. Finally, a discrete firefly algorithm is designed to find the near optional solutions in large dimensions. …”

Weights of sample data. by Yixuan Lu (9987980)

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

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

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

Business priorities. by Yang Yu (4292)

“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”

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

“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”