IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

G<i>m</i>R performance of various HNN-EB<i>k</i>SAT models. by Ghassan Ahmed Ali (17041488)

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Armenia model outputs on optimized resource allocation and health impact by EUHC care package (2019 vs. higher budget scenario). by Nicole Fraser-Hurt (2636833)

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

List of some parameters of the ADA-HNN- EB<i>k</i>SAT model. by Ghassan Ahmed Ali (17041488)

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Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”

Comparison of MAPE mean and RMSE mean for statistical significance. by Ghassan Ahmed Ali (17041488)

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Flow diagram of Wan Abdullah method for HNN. by Ghassan Ahmed Ali (17041488)

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Flowchart for HNN-EB<i>k</i>SAT implementation procedure. by Ghassan Ahmed Ali (17041488)

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Variable importance of features included in the gradient boosting machine learning (XGB) algorithm for predicting postinduction hypotension. by Manabu Yoshimura (11040049)

DATA. by 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. …”

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

“…Finally, an improved RF model is constructed by optimizing the parameters of the RF algorithm. …”

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…However, SDP faces challenges like imbalanced data, high-dimensional features, model overfitting, and outliers. …”

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

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Architecture of proposed system model. by Nanavath Kiran Singh Nayak (22184565)

System model of the proposed method. by Nanavath Kiran Singh Nayak (22184565)

Reducing positional uncertainty by He Wu (22584128)

Proposed CVAE model. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Flowchart of simple ant colony algorithm. by 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. …”

Segmentation results of the proposed model. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”