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--- |
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title: Fricitonangle prediction of solid waste |
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emoji: 🚗 |
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colorFrom: blue |
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colorTo: green |
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sdk: streamlit |
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sdk_version: "1.29.0" |
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app_file: app.py |
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pinned: false |
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--- |
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# Waste Properties Predictor |
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This Streamlit app predicts both friction angle and cohesion based on waste composition and characteristics using deep learning models. |
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## Features |
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- Predicts both friction angle and cohesion simultaneously |
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- Supports Excel file input for batch predictions |
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- Provides SHAP value explanations for predictions |
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- Interactive input interface with value range validation |
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- Supports custom data upload |
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## Files Description |
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- `app.py`: Main application file |
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- `requirements.txt`: Required Python packages |
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- `friction_model.pt`: Pre-trained model for friction angle prediction |
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- `cohesion_model.pt`: Pre-trained model for cohesion prediction |
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- `Data_syw.xlsx`: Default data file with example values |
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## Usage |
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1. The app loads with default values from the first row of `Data_syw.xlsx` |
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2. You can either: |
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- Use the default values |
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- Upload your own Excel file with waste composition data |
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- Manually adjust individual values using the input fields |
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3. Click "Predict Properties" to get predictions and SHAP explanations |
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## Input Parameters |
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The app accepts various waste composition and characteristic parameters. All inputs are validated against the training data ranges to ensure reliable predictions. |
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## Output |
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For each prediction, the app provides: |
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- Predicted friction angle (degrees) |
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- Predicted cohesion (kPa) |
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- SHAP waterfall plots explaining the contribution of each feature to the predictions |
