https://github.com/bamescience/eisnet
https://github.com/bamescience/eisnet
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/bamescience/eisnet
- Owner: BAMeScience
- License: mit
- Created: 2024-05-21T15:53:59.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-21T09:34:32.000Z (9 months ago)
- Last Synced: 2025-01-20T17:20:15.510Z (4 months ago)
- Language: Python
- Size: 1.55 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning-Assisted Equivalent Circuit Identification for Dielectric Spectroscopy of Polymers
## About the Paper
This repository is based on our paper titled "Machine Learning-Assisted Equivalent Circuit Identification for Dielectric Spectroscopy of Polymers." The paper discusses a novel convolutional neural network (CNN) model to predict the electrical equivalent circuit (EEC) topology from broadband dielectric spectroscopy data, enhancing the characterization of polymer membranes' and achieving SOTA resutls.
## Installation
To install the required packages, please run the following command:
```bash
pip install -r requirements.txt
```
## Usage
You can easliy run the model in ```main.py``` and define global parameters.
The file contains the modules required for generating the data ```model.generate_data()``` and pre-processing the data ```model.preprocess_data(data=data)```.\
For training the model, the user can call ```model.Train(Training_data)```, and
for testing the model you can use ```model.Predict(Test_data)```.
Addtionally ```model.Predict(Test_data)``` will save the results in the folder "predictions".