A waterfall plot analysis. حسب Alemu Birara Zemariam (17540938)

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The ROC calibration curve and DCA of the combined prediction model based on CT and MRI. حسب Jiangfa Li (18345033)

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Settings for ABC-SMC code. حسب Román Zapién-Campos (9592478)

S1 Code - حسب Christina M. Homer (3561131)

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"

Table 1_Entropy-adaptive differential privacy federated learning for student performance prediction and privacy protection: a case study in Python programming.docx حسب Shanwei Chen (12031760)

"…This study proposes an Entropy-Adaptive Differential Privacy Federated Learning method (EADP-FedAvg) to enhance the accuracy of student performance prediction while ensuring data privacy. Based on online test records from Python programming courses for Electronic Engineering students (grade 2021–2023) at the School of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, China, the study uses a Multilayer Perceptron (MLP) model and 10 distributed clients for training. …"

The ROC, calibration curve and DCA of the combined prediction model based on tumor diameter combined with the optimal radiomics features. حسب Jiangfa Li (18345033)

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ANFIS model for the four parameters. حسب Ahmed G. Ismail (21519374)

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LHS model for the four parameters. حسب Ahmed G. Ismail (21519374)

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Steering system model. حسب Honglei Pang (22693724)

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Braking system model. حسب Honglei Pang (22693724)

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Partial Rank Correlation Coefficient (PRCC) sensitivity analysis results, obtained using LHS with 1000 samples and run in Python version 3.11.0. حسب Tinashe Victor Mupedza (22022124)

After redistributed load using EMS/ energy storage predicted by LHS with ANFIS. حسب Ahmed G. Ismail (21519374)

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Impact of sensitivity analysis on model performance. حسب Ahmed G. Ismail (21519374)

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Prediction accuracy on varying attack types. حسب Mohanad Faeq Ali (21354273)

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Error in percentage for used hybrid prediction method versus actual. حسب Ahmed G. Ismail (21519374)

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Prediction accuracy analysis over time steps. حسب Mohanad Faeq Ali (21354273)

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<b>Map 104. </b>Distribution of <i>Python natalensis </i>records in south-eastern Zimbabwe. حسب Kurt van Wyk (20481341)

Actual versus hybrid prediction method for (Maximum, Average and Minimum) demand. حسب Ahmed G. Ismail (21519374)

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