SiO2_extraction

This repository contains machine learning models for predicting the degree of SiO2 extraction from iron ore tailings using aqueous solution of ammonium bifluoride (NH4HF2). The prediction models take into account three key parameters: temperature, reaction time, and NH4HF2 concentration.

Models Included

Three different approaches have been implemented:

• Linear Least Squares regression (LS) — worst results
• Random Forest Regressor (RF)
• Fully Connected Artificial Neural Networks (ANN) — best predictions

Repository Structure

*_learning.py — files for model training and testing
*_3D_plot.py — files for result visualization
tf_model.keras — contains the trained ANN model
training_history.json — contains the ANN model's training history

Technical Stack

The programs were developed using:

• Python 3.11.1
• TensorFlow 2.13.0 — for neural network implementation
• Scikit-learn 1.2.2 — for LS and Random Forest models
• Matplotlib 3.6.2 — for data visualization

Installation

1. Install Python from python.org
2. Install the required libraries using pip:

pip install tensorflow==2.13.0
pip install scikit-learn==1.2.2
pip install matplotlib==3.6.2

Additional Information

For a detailed explanation of the methodology, detailed description of the experimental results, data collection, model architectures, and comprehensive analysis of the SiO2 extraction prediction, please refer to our upcoming paper. The link to the article will be provided here once published.

Detailed Windows Installation Guide for Beginners

Step 1: Installing Python

1. Go to the official Python website: https://www.python.org/
2. Click the "Downloads" button and select Python 3.11.1 for Windows
3. Run the downloaded installer file
4. IMPORTANT: In the first installer window, make sure to check "Add Python to PATH"
5. Click "Install Now"
6. Wait for the installation to complete and click "Close"

Step 2: Opening Command Prompt

1. Press the Win + R keys on your keyboard simultaneously
2. In the window that opens, type cmd and press Enter

Step 3: Installing Required Libraries

In the command prompt, enter the following commands one by one (press Enter after each command and wait for the installation to complete):

pip install tensorflow==2.13.0
pip install scikit-learn==1.2.2
pip install matplotlib==3.6.2

Step 4: Download the Repository Files

Download all files from this repository to your computer
Place them in a single folder (for example: C:\Users\YourName\SiO2_extraction)

Step 5: Run One of the Models

Now you can run any of the three models. In the command prompt, navigate to your folder and execute the corresponding command. For example:

python ANN_learning.py
python ANN_3D_plot.py