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

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

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The overlap of Texas Rio Grande Valley Red–crowned Parrot predicted general use, roost site, and nest site habitat distributions as determined using consensus-based feature ensembl... by Elise Varaela Voltura (17592996)

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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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. …”