README.md

---
title: Fricitonangle prediction of solid waste
emoji: 🚗
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: "1.29.0"
app_file: app.py
pinned: false
---


# Waste Properties Predictor

This Streamlit app predicts both friction angle and cohesion based on waste composition and characteristics using deep learning models.

## Features

- Predicts both friction angle and cohesion simultaneously
- Supports Excel file input for batch predictions
- Provides SHAP value explanations for predictions
- Interactive input interface with value range validation
- Supports custom data upload

## Files Description

- `app.py`: Main application file
- `requirements.txt`: Required Python packages
- `friction_model.pt`: Pre-trained model for friction angle prediction
- `cohesion_model.pt`: Pre-trained model for cohesion prediction
- `Data_syw.xlsx`: Default data file with example values

## Usage

1. The app loads with default values from the first row of `Data_syw.xlsx`
2. You can either:
   - Use the default values
   - Upload your own Excel file with waste composition data
   - Manually adjust individual values using the input fields
3. Click "Predict Properties" to get predictions and SHAP explanations

## Input Parameters

The app accepts various waste composition and characteristic parameters. All inputs are validated against the training data ranges to ensure reliable predictions.

## Output

For each prediction, the app provides:
- Predicted friction angle (degrees)
- Predicted cohesion (kPa)
- SHAP waterfall plots explaining the contribution of each feature to the predictions