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Neuro-fuzzy

Description

Neuro-fuzzy is a repository focused on implementing Adaptive Neuro Fuzzy Inference System (ANFIS) for two distinct applications: Capacitive Deionization and Power Prediction.

Capacitive Deionization Example

The Capacitive Deionization example utilizes data with voltage (V), concentrate (ppm), feed rate (ml/min), and electrical conductivity (EC) as input parameters, and Desalination (%) as the output. This ANFIS model aims to predict the desalination percentage based on the provided input data, demonstrating the versatility of neuro-fuzzy systems in water treatment applications.

Power Prediction Example

The Power Prediction example focuses on predicting power consumption using previous values of power and energy. By employing ANFIS, this model forecasts power requirements based on historical data, showcasing the potential of neuro-fuzzy systems in energy forecasting and optimization.

How to Contribute

Contributions to enhance the neuro-fuzzy repository are highly appreciated. Follow these steps to contribute:

  1. Fork the repository.
  2. Create a new branch: git checkout -b feature/your-feature
  3. Implement your changes and commit them: git commit -m 'Add your feature'
  4. Push your branch to the forked repository: git push origin feature/your-feature
  5. Open a pull request detailing the changes you've made.